In some examples, systems and methods for object pairings are provided. For example, a method includes: receiving an input associated with at least one of the one or more first values of one or more weights, the one or more weights corresponding to one or more model parameters associated with a task; determining one or more second values of the one or more weights, at least one second value of the one or more second values of the one or more weights being determined based at least in part on the input; modifying the machine-learning model based on the one or more second values of the one or more weights; determining a plurality of object pairings for the task by applying the modified machine-learning model to data associated with the task, each object pairing of the plurality of object pairings including an asset object and the target object.
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable software for creating, implementing, and managing applications related to categorizing, managing, tracking, and analyzing the relationship between different blocks of data and data sets; Downloadable application programming interface (API) software for creating, implementing and managing applications related to categorizing, managing, tracking, and analyzing the relationship between different blocks of data and data sets; Downloadable software for implementing artificial intelligence and machine learning algorithms and programs concerning the categorization, management, tracking, and analysis of the relationships between different blocks of data and data sets
3.
SYSTEMS AND METHODS FOR PROVIDING CATEGORY-SENSITIVE CHAT CHANNELS
Systems, methods, and non-transitory computer readable media are provided for providing category-sensitive chat channels. A category-sensitive chat channel may be provided. The category-sensitive chat channel may be assigned a given category level. The given category level may determine a scope of content allowed in the category-sensitive chat channel. Information to be posted through the category-sensitive chat channel may be obtained. The obtained information may be filtered based on the given category level. The filtered information may be posted in the category-sensitive chat channel.
Computer-implemented systems and methods are disclosed, including for remotely modifying a configuration file defining a computing environment configuration. A computer-implemented may include, for example, receiving, from a remote server computing device, a configuration file defining a computing environment configuration, parsing the configuration file to generate an indexed data structure, the indexed data structure comprising location identifiers of characters of the configuration file, storing the indexed data structure, generating a graphical user interface based at least in part on the indexed data structure, receiving, via the graphical user interface, a user input indicating a modification to the computing environment configuration, determining, by reference to the indexed data structure and the location identifiers, and based on the user input, one or more changes to the configuration file, and communicating, to the remote server computing device, instructions to update the configuration file in accordance with the one or more changes.
An explorer user interface allows users that are interested in making purpose-based access requests to datasets to view aggregated and/or summary data regarding available datasets prior to making the purpose-based access request. A guided discovery wizard allows a user to view summarized and/or general information regarding datasets and may provide the user options to filter the datasets based on such information and/or based on parameters of specific data items within the datasets (without exposing the specific data items to the user). Thus, the user may filter the datasets to determine a cohort of datasets including data items that are interesting or useful for the specific purpose. The system may provide access to a subset of filtered datasets for the specific purpose in a self-contained, dedicated-purpose directory (an “investigation workspace”) that includes only the precise portion of data that is needed for the requested purpose.
Methods and systems for generating and analyzing visualizations based on a group of sets of data objects. One system includes processors executing instructions to present the sets of data objects in a selectable format on a display device, receive a user selection of a first set of data objects, generate a user interface comprising an indication of the first set of data objects and a plurality of selectable tools to generate a first data visualization of the first set of objects from one or more operations to the first set of objects, receive a user selection of a second set of data objects, receive a user selection to cause the application of the one or more operations to the second set of data objects, and update the user interface to comprise a second visualization based on the one or more operations performed on the second set of data objects.
A computer system can a canonical dataset, a buffer, and an edits dataset. The buffer can dump edits to the edits dataset responsive to one or more conditions. The system can receive a query of the canonical dataset and can rewrite the query to access data from the canonical dataset, the edits dataset, and/or the buffer. The system can execute the query on a combination of data from the canonical dataset, the edits dataset, and/or the buffer, including one or more edits to be made to the canonical dataset.
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
A computer system is disclosed that provides purpose-based control of user actions and access to electronic data assets. For example, the computer system may perform operations including: receiving, from a user, a request to perform an action; determining any checkpoint config objects associated with the action; displaying checkpoint dialog based on checkpoint config object; determining whether criteria associated with the checkpoint object are satisfied; and in response to determining that the criteria associated with the checkpoint object are satisfied: generating a checkpoint record object; and proceeding to perform the action.
A method for management of a production pipeline is disclosed. The method may comprise accessing a data model which comprises a plurality of data objects, including one or more assembly objects, each assembly object representing a part to undergo one or more production events to be performed on a part at a first party facility for providing to a second party facility and one or more production event objects, each production event object representing a particular production event and having a plurality of properties, including an associated start time property and an end time property. The method may also comprise receiving selection of one or more production event objects to be linked to a first assembly object and receiving input of one or more alert conditions to be linked to the first assembly object.
Methods, systems, and non-transitory computer readable media to display a geographical map overlaid with a marker layer comprising at least one marker; receive input from a user to change a zoom level of the geographical map from a first map scale to a second map scale; display the geographical map at the second map scale; and overlay the marker layer at the second map scale with the at least one marker at a second marker size. The second marker size is determined based on a correlation between the second map scale and the second marker size, in which (i) the second marker size is increased or decreased in the same direction as the second map scale when the second map scale is within a range from low threshold point to high threshold point.
G01C 21/36 - Dispositions d'entrée/sortie pour des calculateurs embarqués
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
G06T 3/40 - Changement d'échelle d’images complètes ou de parties d’image, p. ex. agrandissement ou rétrécissement
A search request relating to one or more datasets in the data repository can be received, the search request comprising a display request to display at least a portion of the one or more datasets. In response to the search request, a searchable database can be generated from the one or more datasets in a data repository based on ontological data associated with the one or more datasets. An object view of at least the portion of one or more datasets can be generated from the searchable database, the view being generated based on the ontological data. The generated object view can be provided to be displayed on a display device.
A system and method can provide charter-based access to resources using an object model. Charters are defined by an administrator to have certain markings, each marking indicating a control (e.g., permission, credential, qualification, constraint, requirement, etc.) that regulates work under the charter. Users are also associated with markings. A user starts a session to access the system and is authenticated. The system determines charters having markings that the user has, and these charters are provided to the user to select from. Selecting a charter allows the user access to resources associated with the charter, under the controls indicated by the markings. Charters, controls, qualifications, resources, authorizations and links between them can be implemented using an object model. Markings can control session parameters (e.g., geographic location), resource access, user credentials, qualifications, and/or data processing permissions for a group of users, simplifying project definition and revisions to controlling access under the charter.
A system is programmed to train or fine-tune a large language model (LLM) for converting a user query in natural language to database queries for accessing a set of databases where data related to an ontology is stored. The set of databases includes a graph database and stores metadata and actual data of the ontology. The system is further programed to receive a specific user query exploring links between objects in the ontology and leads to updates to the ontology. The system is programmed to then execute the LLM to obtain a set of database queries, including one or more graph queries. Furthermore, the system is programmed to submit the set of databased queries to the set of databases, which implements the updates to the ontology. The system is then programmed to receive data query results and transmit them in response to the specific user query.
SYSTEMS AND METHODS FOR GENERATING AND DISPLAYING A DATA PIPELINE USING A NATURAL LANGUAGE QUERY, AND DESCRIBING A DATA PIPELINE USING NATURAL LANGUAGE
System and method for generating and displaying data pipelines according to certain embodiments. For example, a method includes: receiving a natural language (NL) query; receiving a model result generated based on the NL query, the model result including a query in a standard query language, the model result being generated using one or more computing models; and generating the data pipeline based at least in part on the query in the standard query language, the data pipeline comprising one or more data pipeline elements, at least one data pipeline element of the one or more pipeline elements being corresponding to a query component of the query in the standard query language.
SYSTEMS AND METHODS FOR GENERATING AND DISPLAYING A DATA PIPELINE USING A NATURAL LANGUAGE QUERY, AND DESCRIBING A DATA PIPELINE USING NATURAL LANGUAGE
System and method for generating and displaying data pipelines according to certain embodiments. For example, a method includes: receiving a natural language (NL) query; receiving a model result generated based on the NL query, the model result including a query in a standard query language, the model result being generated using one or more computing models; and generating the data pipeline based at least in part on the query in the standard query language, the data pipeline comprising one or more data pipeline elements, at least one data pipeline element of the one or more pipeline elements being corresponding to a query component of the query in the standard query language.
Methods, systems, and apparatus, including computer programs encoded on computer storage media for data security protection are provided. One of the methods includes: receiving a job associated with a project, wherein the project is associated with one or more data sources; identifying a plurality of inputs and a plurality of outputs associated with the job; determining a plurality of required permissions associated with the job, wherein each of the required permissions comprises an operation on a required data source, the operation corresponding to at least one of the inputs or the outputs; verifying that the one or more data sources associated with the project comprise the required data source associated with each of the required permissions; and generating a token associated with the job, the token encoding the required permissions associated with the job, wherein the token is required for execution of the job.
In some examples, systems and methods for systems integration are provided. For example, a method includes: receiving a first data asset in a first data format from a first data source; receiving a second data asset in a second data format from a second data source, the second data format being different from the first data format, the second data source being different from the first data source; performing a correlation process to merge the first data asset in the first data format and the second data asset in the second data format to generate a unified data asset in a common data format, the common data format being different from the first data format, the common data format being different from the second data format; and providing the unified data asset in the common data format to a plurality of software applications.
A method performed by one or more processors comprises displaying code, receiving user selection of a portion of code, determining one or more settable data items, generating a template, displaying the template, receiving a user input value for the settable data items by the template, and executing the code with each of the settable data items set to the received user input value. A data processing pipeline is configured to pass a data item to a first transformer to provide first transformed data, store the first transformed data in a temporary memory, write the first transformed data to the data storage system, and pass the transformed data from the temporary memory to a second transformer.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Business data analysis; business consulting services concerning use of data and information by financial institutions, health institutions, non-profit organizations, legal institutions, commercial entities, and government agencies; business data and information consulting services Downloadable software for edge computing, namely, downloadable software for processing data via a distributed computing framework; downloadable edge software using artificial intelligence for processing data via a distributed computing framework; downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; downloadable software for artificial intelligence for use in machine learning, deep learning, natural language generation, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics, business intelligence, and computer vision; downloadable software for knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics and business intelligence; downloadable simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; downloadable software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of data and information; downloadable hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; downloadable software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data and information; downloadable hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; downloadable software for use in advance product research; downloadable computer software development tools; downloadable software for creating, managing, and utilizing ontologies to drive and enable business and operational decisions and actions, workflows, organizational modeling, simulated operations, and collaborative operations and applications; downloadable software for general ledger management; downloadable software for product lifecycle management; downloadable software for enterprise resource planning; downloadable manufacturing execution system software; downloadable software for customer relationship management (CRM); downloadable software for material resource planning; downloadable software for generating, analyzing, and managing data related to engineering bills of materials; downloadable software for generating, analyzing, and managing data related to manufacturing bills of materials; downloadable software for collecting, managing, analyzing, transmitting, storing, sharing, and optimizing the transfer of data over disconnected, denied, intermittent, and limited (DDIL) bandwidth environments; downloadable software for evaluating organizations, determining whether the organizations confirm to established computer security standards, cybersecurity maturity model standards, and data management standards, and for sharing and verifying the aforesaid information; downloadable business process improvement software for optimizing and streamlining manufacturing operations and related maintenance activities; downloadable business process improvement software for optimizing and streamlining digital manufacturing operations and related maintenance activities; downloadable software for vehicle fleet management; downloadable artificial intelligence software for generating real-time insights and operational efficiencies to assist users in scaling manufacturing operations and optimizing related production, supply chain, and logistics functions; downloadable business productivity software for scheduling and workplace collaboration; downloadable software for customizing, maintaining, updating, installing, and deploying other software; downloadable project management software; downloadable software for auditing business activities and business data to facilitate regulatory compliance Providing temporary use of online non-downloadable software for edge computing, namely, for processing data via a distributed computing framework; providing temporary use of online non- downloadable edge software using artificial intelligence software for processing data via a distributed computing framework; providing temporary use of online non-downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; providing temporary use of online non-downloadable artificial intelligence software for machine learning, deep learning, natural language generation, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics, business intelligence, and computer vision; providing temporary use of online non-downloadable software, namely, non-downloadable software for knowledge- based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics and business intelligence; providing temporary use of online non-downloadable simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; providing temporary use of online non-downloadable software for artificial intelligence, namely, for use in data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, machine learning, deep learning, natural language generation, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics, business intelligence, and computer vision; providing temporary use of online non-downloadable knowledge-based artificial intelligence software platforms, data analytics software platforms, and automation software platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics and business intelligence; advanced product research; providing temporary use of online non-downloadable software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of data and information; providing temporary use of online non-downloadable software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data and information; providing temporary use of online non-downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; scientific and technological services, namely, scientific research; scientific and technological research and development; information technology consultation and research; custom software engineering services and software design; software design and development; providing temporary use of online non-downloadable hosting software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; providing temporary use of online non-downloadable software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, security, and tracking of geospatial, map and location data; providing temporary use of online non- downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining of geospatial, map and location data and information; providing temporary use of online non-downloadable software development tools; providing temporary use of online non-downloadable software featuring software platforms for creating, managing, and utilizing ontologies to drive and enable business and operational decisions and actions, workflows, organizational modeling, simulated operations, and collaborative operations and applications; providing temporary use of online non-downloadable software for general ledger management; providing temporary use of online non-downloadable software for product lifecycle management; providing temporary use of online non-downloadable software for enterprise resource planning; providing temporary use of online non-downloadable manufacturing execution system software; providing temporary use of online non-downloadable software for customer relationship management (CRM); providing temporary use of online non-downloadable software for material resource planning; providing temporary use of online non-downloadable software for generating, analyzing, and managing data related to engineering bills of materials; providing temporary use of online non-downloadable software for generating, analyzing, and managing data related to manufacturing bills of materials; providing temporary use of online non-downloadable software for collecting, managing, analyzing, transmitting, storing, sharing, and optimizing the transfer of data over disconnected, denied, intermittent, and limited (DDIL) bandwidth environments; providing temporary use of online non-downloadable software for evaluating organizations, determining whether the organizations confirm to established computer security standards, cybersecurity maturity model standards, and data management standards, and for sharing and verifying the aforesaid information; providing temporary use of online non-downloadable business process improvement software for optimizing and streamlining manufacturing operations and related maintenance activities; providing temporary use of online non-downloadable business process improvement software for optimizing and streamlining digital manufacturing operations and related maintenance activities; providing temporary use of online non-downloadable software for vehicle fleet management; providing temporary use of online non-downloadable artificial intelligence software for generating real-time insights and operational efficiencies to assist users in scaling manufacturing operations and optimizing related production, supply chain, and logistics functions; providing temporary use of online non-downloadable business productivity software for scheduling and workplace collaboration; providing temporary use of online non-downloadable software for customizing, maintaining, updating, installing, and deploying other software; providing temporary use of online non-downloadable project management software; providing temporary use of online non-downloadable software for auditing business activities and business data to facilitate regulatory compliance
Systems, methods, and non-transitory computer readable media are provided for generating or obtaining situations in which scores indicative of a danger or a hazard exceeds a threshold, receiving a selection of a first situation, in response to receiving the selection of the first situation, obtaining intelligence data, asset data, and operational data, analyzing the intelligence data using a trained machine learning model for the first situation; and determining a response measure based on the analyzed intelligence data.
A system comprising a computer-readable storage medium storing at least one program and a method for integrating collaborative spreadsheet data into one or more network applications is presented. The method may include accessing an application data schema comprising a set of constraints on application data consumed by an application hosted by an application server. The method may further include accessing a spreadsheet having one or more data validation rules. The method may further include determining whether the one or more data validation rules include the set of constraints. In response to determining the one or more data validation rules include the set of constraints, application data consumed by the application is synchronized with spreadsheet data corresponding to the spreadsheet.
G06F 40/18 - Édition, p. ex. insertion ou suppression de tableauxÉdition, p. ex. insertion ou suppression utilisant des lignes réglées de tableurs
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/14 - Sortie numérique vers un dispositif de visualisation
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
H04L 67/1095 - Réplication ou mise en miroir des données, p. ex. l’ordonnancement ou le transport pour la synchronisation des données entre les nœuds du réseau
A computer system is disclosed that provides purpose-based access to electronic data assets. For example, the computer system may perform operations including: receiving, from a first user, a request to access data assets associated with a purpose object; in response to receiving the request from the first user: generating a purpose access request object including at least an identification of the first user and an identification of the purpose object; and providing an indication of the purpose access request object to a second user associated with the purpose object; receiving, from the second user, an approval of the request; and in response to receiving the approval of the request from the second user: updating the purpose access request object to include at least an indication of the approval of the request; and granting the first user access to data assets associated with the purpose object.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
25.
SYSTEMS AND METHODS FOR GENERATING AND DISPLAYING A DATA PIPELINE USING A NATURAL LANGUAGE QUERY, AND DESCRIBING A DATA PIPELINE USING NATURAL LANGUAGE
System and method for generating and displaying data pipelines according to certain embodiments. For example, a method includes: receiving a natural language (NL) query; receiving a model result generated based on the NL query, the model result including a query in a standard query language, the model result being generated using one or more computing models; and generating the data pipeline based at least in part on the query in the standard query language, the data pipeline comprising one or more data pipeline elements, at least one data pipeline element of the one or more pipeline elements being corresponding to a query component of the query in the standard query language.
A method of managing digital entities in data repositories comprises storing one or more data objects in a non-graph data repository into one or more nodes and edges of a graph, comprising transforming an access control list (ACL) of a first data object into an ACL node and transforming a version of a second data object into a version node in a graph data repository; electronically receiving a search query associated with a user account for a shortest path between two specified nodes of the graph; executing the search query against the graph data repository to generate a result set of nodes including only nodes corresponding to most recent versions of the one or more data objects that are visible to the user account under applicable ACLs.
Example embodiments involve a metrics collection system for collecting software usage metrics from one or more client devices at deployments. A computer, such as a server configured to execute the metrics collection system, collects software usage metrics (e.g., as a metrics submission from a client device) of the software product at the deployment, identifies a metrics type of the software usage metrics collected, assigns the software usage metrics to a metrics category, and calculates and updates a metrics score of the metrics category, based on the software usage metrics collected.
H04N 1/00 - Balayage, transmission ou reproduction de documents ou similaires, p. ex. transmission de fac-similésLeurs détails
H04L 43/045 - Traitement des données de surveillance capturées, p. ex. pour la génération de fichiers journaux pour la visualisation graphique des données de surveillance
H04L 67/12 - Protocoles spécialement adaptés aux environnements propriétaires ou de mise en réseau pour un usage spécial, p. ex. les réseaux médicaux, les réseaux de capteurs, les réseaux dans les véhicules ou les réseaux de mesure à distance
Methods and systems for enhanced techniques for building user interfaces. An example method includes presenting a builder user interface to create a consumer user interface. The builder user interface receives information usable to filter data objects associated with a data object type. The information includes a variable associated with a property indicated by the data object type and the variable is associated with a first user interface element of the consumer user interface. An association between a second user interface element included in the consumer user interface and presentation of information generated based on data objects is received. Adjustment of the first user interface element causes filtering of the data objects via adjustment of the variable updating of the information. Access to the consumer user interface is enabled.
G06F 3/04845 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs pour la transformation d’images, p. ex. glissement, rotation, agrandissement ou changement de couleur
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
Computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for generating data objects and/or updating an ontology. A computer-implemented method may include: employing one or more large language models (“LLMs”) to generate at least a data triple and a classified triple; executing, using the classified triple, a similarity search with reference to an ontology to determine that the classified triple at least partially matches one or more data object types defined in the ontology; in response to the determination, adding into a first database at least a first data object of a first data object type that represents a first entity in the data triple and a second data object of a second data object type that represents a second entity in the data triple.
G06F 18/2415 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques basées sur des modèles paramétriques ou probabilistes, p. ex. basées sur un rapport de vraisemblance ou un taux de faux positifs par rapport à un taux de faux négatifs
G06N 3/0895 - Apprentissage faiblement supervisé, p. ex. apprentissage semi-supervisé ou auto-supervisé
30.
RESOURCE DEPENDENCY SYSTEM AND GRAPHICAL USER INTERFACE
A resource dependency system and its associated user interfaces, used for tracking data dependencies and data transformations between resources, may display visual node graphs with resources as nodes and the data dependencies and data transformations associated with the columns as edges between the nodes. The nodes representing the resources may be displayed differently based on relevant differences in the resources they represent, which can be set through various selectable criteria and schemes.
G06F 16/909 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
G06N 7/01 - Modèles graphiques probabilistes, p. ex. réseaux probabilistes
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
Aspects of the present disclosure relate to computer system security. A machine accesses a set of records corresponding to a set of users having access to a computer system. The machine stores, for each user in the set of users, a baseline profile representing baseline activity of the user with respect to a set of data sources of the computer system. The machine monitors activity of the set of users with respect to the set of data sources. The machine determines, based on monitoring the activity of the set of users, that a user action of a specified user, with respect to one or more data sources from the set of data sources, is anomalous relative to the baseline profile of the specified user. The machine provides a digital transmission representing the anomalous user action.
Disclosed herein are systems and methods for generating notional data. The method includes: receiving seed data of one or more object types in a base dataframe; defining one or more functional relationships associated with the one or more object types, at least one functional relationship of the one or more functional relationships specifying a change to seed data of one object type of the one or more object types; generating data of the one or more object types based at least in part on the seed data in the base dataframe and the one or more functional relationships; and generating the notional data based at least in part on the generated data of the one or more object types.
Systems and methods are provided for coordinating the deployment of frontend assets to defined user groups. Individual groups of users may be assigned to a track comprising a set of frontend assets. Each set of frontend assets may comprise each of the individual components required to generate an entire frontend for an application. In some embodiments, different versions of a single component may be assigned within different tracks. As such, one set of users may be provided a first version of an application and a second set of users may be provided a second version of that application. By associating a new or updated version of a component to a given track, a new or updated version of a component not yet ready for widespread deployment may be provided to only a limited number of users.
Methods and systems for providing a user interface and workflow for interacting with time series data, and applying portions of time series data sets for refining regression models. A system can present a user interface for receiving a first user input selecting a first model from a list of models for modeling the apparatus, generate and display a first chart depicting a first time series data set depicting data from a first sensor, generate and display a second chart depicting a second time series data set depicting a target output of the apparatus, receive a second user input of a portion of the first time series data set, and generate and display a third chart depicting a third time series data set depicting an output of the selected model and aligned with the second chart of the target output and updated in real-time in response to the second user input.
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Business data analysis; business consulting services concerning use of data and information by financial institutions, health institutions, non-profit organizations, legal institutions, commercial entities, and government agencies; advisory services relating to information and data processing Providing non-downloadable operating system software; providing non-downloadable software using artificial intelligence to empower integration of data, operations and decision-making; providing non-downloadable software for edge computing; providing non-downloadable edge artificial intelligence software; providing non-downloadable software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; providing non-downloadable software for artificial intelligence, machine learning, deep learning, natural language generation, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics, business intelligence, and computer vision; providing non-downloadable software, namely, knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics and business intelligence; providing non-downloadable simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; providing non-downloadable software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, hosting, security, and tracking of data and information; providing non-downloadable software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, hosting, security, and tracking of geospatial, map and location data and information; software as a service (SaaS) featuring software for data processing, data storage, data capture, data collection, data validation, data security, data warehousing, data management, and data mining; software as a service (SaaS) featuring software for artificial intelligence, machine learning, deep learning, natural language generation, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics, business intelligence, and computer vision; software as a service (SaaS) featuring knowledge-based artificial intelligence platforms, data analytics platforms, and automation platforms for use in the fields of artificial intelligence, machine learning, deep learning, statistical learning, supervised learning, un-supervised learning, data mining, predictive analytics and business intelligence; software as a service (SaaS) featuring simulation, modeling and data processing software for use in data visualization, data analysis, data mining, data interpretation, predictive analytics, accessing and editing large-scale data, interactive visual computing, and design of information graphics; software as a service (SaaS) featuring software for information and data integration, analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, hosting, security, and tracking of data and information; software as a service (SaaS) featuring software for analysis, management, collaboration, algorithmic and human-driven exploration, viewing, modeling, exporting, visualization, organization, modification, book marking, transmission, storage, exchange, sharing, querying, auditing, collection, editing, hosting, security, and tracking of geospatial, map and location data and information; software as a service (SaaS) featuring operating system software; software as a service (SaaS) featuring software using artificial intelligence to empower integration of data, operations and decision-making; advanced product research in the field of artificial intelligence; scientific and technological research and analysis in the field of national security; scientific and technological research and development in the field of national security; technology consultation and research in the field of national security; advance product research in the field of national security; engineering and design in the field of national security; software design and development in the field of national security; providing non-downloadable software for use in scientific and technological research and analysis in the field of national security; providing non-downloadable software for use in scientific and technological research and development in the field of national security; providing non-downloadable software for use in technology consultation and research in the field of national security; providing non-downloadable software for use in advance product research in the field of national security; providing non-downloadable software for use in engineering and design in the field of national security
Systems, techniques, and user interfaces are disclosed for an object-centric builder software that can utilize an ontology to design, configure, and build a workflow application that also references the ontology to perform a workflow. The ontology may serve as a data model for stored data associated with the particular workflow. The builder software may leverage the ontology to obtain advance knowledge of the availability and structure of the stored data that will be accessible to the workflow application at run-time, in order to build a workflow application that is well-tailored for that particular workflow. This approach may also result in flexible workflow applications that are easily built and maintained.
Computing systems methods, and non-transitory storage media are provided for obtaining images, extracting layers from each of the images, extracting segments from each of the layers, generating a compressed version of the segments by storing a single copy of each segment and metadata to reconstruct the layers from the segments and the images from the layers, and simulating a reconstruction of the image from the compressed version.
A system may receive a first user input requesting to provide an evaluator agent configuration for an evaluator agent. A system may receive a second user input specifying information associated with an agent to be evaluated. A system may receive a third user input specifying an evaluation tool, wherein the evaluation tool is configurable to evaluate the information associated with the agent. A system may receive a fourth user input specifying an evaluation tool configuration associated with the evaluation tool. A system may create the evaluator agent based on the evaluator agent configuration, wherein the evaluator agent configuration comprises an indication of the information associated with the agent to be evaluated, an indication of the evaluation tool, and an indication of the evaluation tool configuration. A system may include evaluating, using the evaluator agent, the information associated with the agent.
A method of providing ingress control comprises managing one or more replicas of an application on a software platform; creating an annotation resource that includes one or more annotations for the software platform; creating an ingress resource for a specific annotation of the one or more annotations, the specific annotation being in a specification for the application; receiving a request to access the application from a device external to the software platform, the request matching the specific annotation; and routing the request to a replica of the one or more replicas based on the ingress resource.
System and method for terminating instances and autoscaling instance groups of computing platforms. For example, a method includes determining whether an instance of an instance group is identified as eligible for termination. The method further includes, in response to determining that the instance of the instance group is identified as eligible for termination, terminating the eligible instance. The terminating the eligible instance includes, in response to a runtime of the eligible instance being equal to or larger than a predetermined maximum lifetime, terminating the eligible instance. The terminating the eligible instance further includes, in response to the runtime being smaller than the predetermined maximum lifetime, detaching the eligible instance from the instance group to allow a new instance to be associated with the instance group, and in response to the eligible instance being detached from the instance group: waiting for the new instance to be associated with the instance group, and evicting each pod associated with the detached instance. The method is performed using one or more processors.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
42.
SYSTEMS AND METHODS FOR GENERATING AND DISPLAYING A DATA PIPELINE USING A NATURAL LANGUAGE QUERY, AND DESCRIBING A DATA PIPELINE USING NATURAL LANGUAGE
System and method for generating and displaying data pipelines according to certain embodiments. For example, a method includes: receiving a natural language (NL) query; receiving a model result generated based on the NL query, the model result including a query in a standard query language, the model result being generated using one or more computing models; and generating the data pipeline based at least in part on the query in the standard query language, the data pipeline comprising one or more data pipeline elements, at least one data pipeline element of the one or more pipeline elements being corresponding to a query component of the query in the standard query language.
Systems and methods are provided for enhanced machine learning refinement and alert generation. An example method includes accessing datasets storing customer information reflecting transactions of customers. Individual risk scores are generated for the customers based on the customer information. Generating the risk score includes providing identified occurrences of scenario definitions and customer information as input to one or more machine learning models, the scenario definitions identifying occurrences of specific information reflected in the datasets, with the machine learning models assign respective risk scores to the customers. An interactive user interface is presented. The interactive user presents summary information associated with the risk scores, with the interactive user interfaces enabling an investigation into whether a particular customer is exhibiting risky behavior, responds to user input indicating feedback usable to update the one or more machine learning models or scenario definitions, with the feedback triggering updating of the machine learning models.
Systems and methods for implementing sequenced filter templates to intelligently reduce a dataset to find useful patterns and source data are disclosed. An expert investigative user may configure a filter template comprising a series of filters organized in a sequence desired by the expert user. The filter template can be customized by an end user to reduce a dataset and perform guide investigation of the reduced dataset.
Example embodiments described herein pertain to a geographic information system (GIS), configured to obtain geospatial data representing a geographic area, assign a projection and coordinate system to the geospatial data, apply a transformation to the geospatial data, and generate a tile cache based on the transformed geospatial data, the tile cache including the determined projection and coordinate system.
G06F 16/955 - Recherche dans le Web utilisant des identifiants d’information, p. ex. des localisateurs uniformisés de ressources [uniform resource locators - URL]
G06F 16/957 - Optimisation de la navigation, p. ex. mise en cache ou distillation de contenus
G06T 3/14 - Transformations pour le recalage d’images, p. ex. ajustement ou mappage pour l’alignement d’images
G06T 3/40 - Changement d'échelle d’images complètes ou de parties d’image, p. ex. agrandissement ou rétrécissement
G06T 3/60 - Rotation d’images entières ou de parties d'image
Disclosed herein are systems and techniques for centralized data retention and deletion. Data can be ingested from multiple external data sources and saved internally for use to process data modification (e.g., deletion) requests via a data processing pipeline, which may apply eligibility checks and modification logic to determine the appropriate modifications to the relevant data items to comply with the data modification request. Various user interfaces may be generated to provide a user with oversight of the data processing pipeline and the data modifications. The user may review and trigger the modification of data stored at the external data sources and/or internally.
A model management system provides a centralized repository for storing and accessing models. The model management system receives an input to store a model object in a first model state generated based on a first set of known variables. The model management system generates a first file including a first set of functions defining the first model state and associates the first file with a model key identifying the model object. The model management system receives an input to store the model object in a second model state having been generated based on the first model state and a second set of known variables. The model management system generates a second file including a second set of functions defining the second model state and associates the second file with the model key. The model management system identifies available versions of the model object based on the model key.
G06F 30/00 - Conception assistée par ordinateur [CAO]
G06F 111/20 - CAO de configuration, p. ex. conception par assemblage ou positionnement de modules sélectionnés à partir de bibliothèques de modules préconçus
G06N 7/00 - Agencements informatiques fondés sur des modèles mathématiques spécifiques
48.
ENHANCED PROCESSING OF TIME SERIES DATA VIA PARALLELIZATION OF INSTRUCTIONS
Systems and methods are provided for enhanced processing of time series data via parallelization of instructions. An example method includes receiving a query indicating time series datasets and operations to be performed on the time series datasets. Nodes associated with the query are identified, with each node associated with a time series dataset. Nodes associated with operations to be performed are generated. The nodes are assembled into query tree, with parent nodes of the query tree indicating operations that are to be applied to children nodes. Instructions for processing the query tree are generated. At least a subset of the instructions is provided to one or more compute systems for processing in parallel. Results are received, and presented in a user interface.
G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
G06F 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
49.
CONTINUOUS BUILDS OF DERIVED DATASETS IN RESPONSE TO OTHER DATASET UPDATES
A method comprises creating and storing a dependency graph representing at least one derived dataset and one or more raw datasets or intermediate derived datasets on which the at least one derived dataset depends; reading configuration data specifying one or more periods; detecting, at a first unscheduled time, a first update to a first dataset among the one or more raw datasets or intermediate derived datasets, the first dataset being a beginning of a series of derived datasets ending with a final dataset; initiating a first transformation of the first dataset to generate a first intermediate derived dataset; detecting, at a second unscheduled time, a second update to the first dataset; determining that a throttle condition specified in the configuration data is not met; initiating, when the final dataset is not yet built in response to the first update, a second transformation of the first dataset.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
50.
GENERALIZABLE ENTITY RESOLUTION BASED ON ONTOLOGY STRUCTURES
A system for managing entity resolution processes is disclosed. The system is programmed to determine whether incoming records correspond to known entities within an ontology framework. The system is also programmed to manage a graphical user interface that allows customizing entity resolution operations and providing feedback on the determination results. The system is further programmed to use the provided feedback to improve machine learning for the entity resolution processes.
An asset owner may be interested in determining risks associated with physical assets, such as to damage or other loss associated with the assets. Accurately identifying such risks may be useful in determining preventative actions that may be taken to reduce data or loss associated with the assets. The systems and methods described herein generally relate to automating a process of obtaining data regarding physical assets, such as from sensors associated with the assets, determining one or more risk indicators associated with the assets, and initiating some actions based on the determined risk indicators.
A system for automated processing and analysis of audio files for large data sets in a cloud environment. A unified analytic environment can integrate audio machine learning models for processing and analysis with a knowledge management system, including graph presentations of tracked entities, linked to audio files and/or associated translations and transcripts. Entities within such data can be searched or filtered and proposed for tracking, or identified as tracked objects. These features can allow triage and prioritization of audio files for analysis. User interfaces can facilitate feedback on transcription and translation outputs, thereby improving present outputs and future inputs and outputs. Entities speaking or referred to can be found, tagged, and distinguished in audio files (e.g., using speaker identification in audio files, text searching in transcripts, etc.) Users can provide feedback and input on various aspects of a system, to enhance or adjust initial automated or other machine learning outputs.
G06F 40/58 - Utilisation de traduction automatisée, p. ex. pour recherches multilingues, pour fournir aux dispositifs clients une traduction effectuée par le serveur ou pour la traduction en temps réel
G10L 17/04 - Entraînement, enrôlement ou construction de modèle
G10L 21/028 - Séparation du signal de voix utilisant les propriétés des sources sonores
53.
RESOURCE DEPENDENCY SYSTEM AND GRAPHICAL USER INTERFACE
A resource dependency system displays two dynamically interactive interfaces in a resource dependency user interface, a hierarchical resource repository and a dependency graph user interface. User interactions on each interface can dynamically update either interface. For example, a selection of a particular resource in the dependency graph user interface causes the system to update the dependency graph user interface to indicate the selection and also updates the hierarchical resource repository to navigate to the appropriate folder corresponding to the stored location of the selected resource. In another example, a selection of a particular resource in the hierarchical resource repository causes the system to update the hierarchical resource repository to indicate the selection and also updates the dependency graph user interface to display an updated graph, indicate the selection and, in some embodiments, focus on the selected resource by zooming into a portion of the graph.
A method of managing decoupled front-end and back-end processes is disclosed. The method comprises receiving a first result of user interaction with a first front-end interface; determining that the first result represents a validation of a data item entered via the first front-end interface; mapping the data item in a validated form to a back-end object; causing storing the data item in a database system in association with the back-end object; receiving a second result of user interaction with a second front-end interface; determining that the second result represents a state transition corresponding to executing a query entered via the second front-end interface against the database system; mapping the state transition to a set of back-end commands; causing executing the set of back-end commands over the database system of back-end objects.
A computer system provides transaction-level data retention policy inheritance. The system may perform operations including storing a first dataset comprising a plurality of transactions, each of the plurality of transactions comprising one or more data items; receiving a first transaction to the first dataset, the first transaction comprising one or more data items; determining a first retention policy for the first transaction; and storing the first retention policy with the first transaction. The system may further perform operations including calculating a deletion date for the first transaction based on the first retention policy; and storing the deletion date with the first transaction in the first dataset.
Systems are provided for managing access to a log of dataset that is generated when the dataset is accessed. A system stores, with respect to each of a log producer and a log accessor, an encrypted symmetric key for dataset that is encrypted using a corresponding public key. The system returns the encrypted symmetric key for the log producer, such that the log producer can decrypt the dataset that is encrypted using the symmetric key. A log of the dataset is generated when the log producer accesses the dataset.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
H04L 9/32 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité comprenant des moyens pour vérifier l'identité ou l'autorisation d'un utilisateur du système
Systems, methods, and non-transitory computer readable media are provided for using linked documents. A system may receive, from a computing device, a request for a document. Content of the document may be defined based on state information and stateless information. A system may determine a local replica of the document in a local database. The local replica of the document may be linked to a primary replica of the document. The local replica of the document may include a snapshot of the primary replica of the document. The primary replica of the document may be stored in a remote database which may be accessible through a remote server. The system may subscribe to the primary replica of the document through the remote server, and may provide access to the document to the computing device based at least in part on the subscription to the primary replica of the document.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 17/14 - Transformations de Fourier, de Walsh ou transformations d'espace analogues
H04L 67/1095 - Réplication ou mise en miroir des données, p. ex. l’ordonnancement ou le transport pour la synchronisation des données entre les nœuds du réseau
Computer-implemented systems and methods including language models for explaining and resolving code errors. A computer-implemented method may include: receiving or accessing a log comprising an error message, the error message indicating an error in code; determining the error message from the log; determining a context associated with the error; generating a prompt for a large language model (“LLM”), the prompt comprising at least: the error message, and the context associated with the error; transmitting the prompt to the LLM; and receiving an output from the LLM in response to the prompt, the output comprising at least: an explanation of the error message, and a suggested fix for the error.
Systems and methods are provided for creating and managing a data integration workspace. The workspace may comprise one or more views of data (or datasets) stored in or accessible by the system. Models may be generated and updated based on the plurality of datasets and presented via a graphical user interface. Feedback received via a graphical user interface presenting a model may be used to annotate an underlying dataset associated with the model. Responsive to a modification of the underlying dataset or the rules for using the underlying dataset to generate the model, other related datasets and/or models may be automatically updated accordingly. Templates associated with one or more types of users may be defined. Each template may comprise one or more specific models related to a specific type of user.
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 16/21 - Conception, administration ou maintenance des bases de données
Computing systems methods, and non-transitory storage media are provided for receiving a first representation of an unstructured data entity. The first representation includes an indication of a detection. The unstructured data entity is part of a corpus. Next, second representations of the unstructured data entity are received and resolved according to a consensus. Next, any discrepancies between the first representation and the resolved second representations are determined. The any discrepancies include any difference in an existence or an absence of the detection, in a relative position of the detection, or in a type or a classification of the detection. Next, feedback regarding the any discrepancy is received. Next, the first representation is selectively modified, or selectively prompted to be modified, based on the any discrepancy and the feedback.
A user interface for working through workflows can include a dual-region approach. The first display region can display a series of workflows that an assigned worker (“assignee”) may have. Each of the workflows can have one or more tasks associated therewith. Each workflow and/or task can be associated with one or more triggers that initiate the assignment of that workflow and/or task. In response to selection of a workflow or task, the second display region can display information associated with the workflow or task.
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
Systems and methods are provided for intelligently monitoring environments, classifying objects within such environments, detecting events within such environments, receiving and propagating input concerning image information from multiple users in a collaborative environment, identifying and responding to situational abnormalities or situations of interest based on such detections and/or user inputs.
Systems and methods are provided for obtaining a media, the media including an image, audio, video, or combination thereof. An input may be received regarding one or more features or frames of the media to be maintained in or removed from the media. One or more criteria of a lossy compression technique may be inferred based on the received input, using a machine learning model, based on the received input. The inferred criteria of the lossy compression technique may be applied to the media.
G06T 3/40 - Changement d'échelle d’images complètes ou de parties d’image, p. ex. agrandissement ou rétrécissement
G10L 19/00 - Techniques d'analyse ou de synthèse de la parole ou des signaux audio pour la réduction de la redondance, p. ex. dans les vocodeursCodage ou décodage de la parole ou des signaux audio utilisant les modèles source-filtre ou l’analyse psychoacoustique
A method may comprise receiving a query for performing one or more computational operations on one or more multi-dimensional data sets representing multi-dimensional time series data collected in real-time from one or more sensors associated with one or more technical systems. The method may also comprise identifying the location of the one or more multi-dimensional time series data sets in one or more databases, retrieving the one or more multi-dimensional time series data sets from the identified one or more databases, and performing the one or more computational operations on the retrieved one or more multi-dimensional time series data sets. The method may also comprise generating output based on the result of the one or more computational operations indicative of one or more states of the one or more technical systems with respect to time.
Disclosed herein are methods and systems for interacting with data in a data repository. After automatically populating one or more display elements with data items from a first dataset, one or more unpopulated display elements can be identified that can be populated with one or more additional data items from another dataset in a data repository. A second dataset that is joined to the first dataset can be identified based on template definitions associated with the display elements. The second dataset can include the one or more additional data items corresponding to the one or more unpopulated display elements. The one or more unpopulated display elements can be populated with the one or more additional data items retrieved from the second dataset to update the graphical user interface.
Systems and methods provide an interface for accessing a data analysis workbook through which data is accessed and manipulated using a plurality of programming languages and application programming interfaces (APIs). Input data on which one or more data transformations are to be performed within the data analysis workbook is accessed, wherein the input data corresponds to a first object representation of a dataset, and wherein the one or more data transformations require the dataset to be a different, second object representation of the dataset. The second object representation of the dataset can be extracted from the first object representation of the dataset through a first language delegate that manages data associated with the first object representation. The one or more data transformations can be applied to the extracted second object representation of the dataset through a different, second language delegate that manages data associated with the second object representation.
Systems and methods are provided for generating and storing data snippets. A data file can be obtained from a data source through a plug-in interface. The data file can be played to a user through an application running on a computing device. An indication can be received from the user, through the application, to tag an entity depicted in the data file during playback of the data file. A snippet of the data file can be stored, wherein the snippet is a portion of the data file corresponding to the entity tagged by the user.
H04N 21/84 - Génération ou traitement de données de description, p. ex. descripteurs de contenu
G06F 16/48 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/483 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
H04N 21/845 - Structuration du contenu, p. ex. décomposition du contenu en segments temporels
68.
SYSTEM AND METHOD FOR SELECTING MACHINE LEARNING TRAINING DATA
Systems and methods are provided for selecting training examples to increase the efficiency of supervised active machine learning processes. Training examples for presentation to a user may be selected according to measure of the model's uncertainty in labeling the examples. A number of training examples may be selected to increase efficiency between the user and the processing system by selecting the number of training examples to minimize user downtime in the machine learning process.
Described herein are systems, methods, and non-transitory computer readable media for validating or rejecting automated detections of an entity being tracked within an environment in order to generate a track representative of a travel path of the entity within the environment. The automated detections of the entity may be generated by an artificial intelligence (AI) algorithm. The track may represent a travel path of the tracked entity across a set of image frames. The track may contain one or more tracklets, where each tracklet includes a set of validated detections of the entity across a subset of the set of image frames and excludes any rejected detections of the entity. Each tracklet may also contain one or more user-provided detections in scenarios in which the tracked entity is observed or otherwise known to be present in an image frame but automated detection of the entity did not occur.
G06V 10/94 - Architectures logicielles ou matérielles spécialement adaptées à la compréhension d’images ou de vidéos
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
G06V 10/774 - Génération d'ensembles de motifs de formationTraitement des caractéristiques d’images ou de vidéos dans les espaces de caractéristiquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant l’intégration et la réduction de données, p. ex. analyse en composantes principales [PCA] ou analyse en composantes indépendantes [ ICA] ou cartes auto-organisatrices [SOM]Séparation aveugle de source méthodes de Bootstrap, p. ex. "bagging” ou “boosting”
G06V 20/52 - Activités de surveillance ou de suivi, p. ex. pour la reconnaissance d’objets suspects
A collaborative planning system facilitates sharing of critical plans (e.g., a military mission plan) within an organization and managing authorizations of the plans from reviewers at multiple levels within the organization. Once the plans are approved, a data object representative of the plans is created and stored in an ontology of data objects (with objects of various types and associations between related data objects) so that the plans may be identified as associated with related data objects via searches of the data objects in the ontology.
A method of handling a dataset for a build pipeline comprises receiving, from a build service, a query for information related to a dataset being in a first format not managed by the build service for a build pipeline; providing, to the build service, first information related to change in the dataset since a last build performed by the build service in a second format managed by the build service, the first information indicating a version of the dataset used in the last build; transmitting, to the build service, a request for information regarding a new build performed based on the first information; receiving, from the build service, second information regarding the dataset generated from the new build in the second format; storing a new version of the dataset in the first format based on the second information.
A system architecture for linking one or more derived objects to existing data objects in a data structure can be organized in a variety of forms. A method for establishing the architecture may include linking first and second data objects. linking first and second data objects. The first and second data objects may be associated with corresponding first and second pluralities of properties. The method may include receiving a first user limitation associated with at least one of the first or second pluralities of properties and receiving a second user limitation associated with at least one of the first or second pluralities of properties. The method can include deriving a conclusion object comprising a third plurality of properties comprising a subset of one or more of the first or second pluralities of properties and linking the conclusion object to the first and second data objects.
Systems and methods for a central user interface for accessing, and upgrading of, dataset integrations. An example method includes accessing, by a system of one or more processors, datasets stored via respective outside devices or systems. The datasets are integrated by the system according to respective integration tiers, with each integration tier being associated with, at least, a respective subset of search functionality enabled via the system. An interactive user interface is presented via a user device, with the interactive user interface presenting summary information. The interactive user interface further enables adjustment of a particular dataset from a first integration tier to a second integration tier.
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
G06F 16/26 - Exploration de données visuellesNavigation dans des données structurées
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 16/28 - Bases de données caractérisées par leurs modèles, p. ex. des modèles relationnels ou objet
The present disclosure relates to methods and systems for querying data in a data repository. According to a first aspect, this disclosure describes a method of querying a database, comprising: receiving, at a computing device, a plurality of keywords; determining, by the computer device, a plurality of datasets relating to the keywords; identifying, by the computer device, metadata for the plurality of datasets indicating a relationship between the datasets by examining an ontology associated with the datasets; providing, by the computer device, one or more suggested database queries in natural language form, the one or more suggested database queries constructed based on the plurality of keywords and the metadata; receiving, by the computing device, a selection of the one or more suggested database queries; and constructing, by the computer device, an object view for the plurality of datasets based on the selected query and the metadata.
Computer-implemented systems and methods are disclosed, including systems and methods for automatically solving problems. A computer-implemented method may include: by an agent service configured to interact with an LLM to complete a run: providing an LLM with access to a state machine, executing an initial state of the state machine with the LLM, determining a subsequent state of the state machine based on at least an initial LLM output, and executing the subsequent state of the state machine.
Computer-implemented systems and methods are disclosed, including systems and methods for automatically solving computational tasks or problems. A computer-implemented method may include: providing an agent service that utilizes a plurality of agents to process one or more tasks; receiving, by a first agent, a request to handle a first task; obtaining, by the first agent, a first accessory to handle the first task; assigning, by the first agent, at least a portion of the first task to a second agent; sharing, by the first agent, the first accessory to the second agent; and processing, by the second agent, at least the portion of the first task using the first accessory to generate a processing result.
A computer system may be configured to: execute a first query associated with a first panel; display the first panel in a user interface based on first display settings of the first panel, the first panel displaying at least a portion of the result of the first query, the result of the first query associated with a variable; execute a second query associated with a second panel, wherein the second query refers to the variable associated with the first query; display the second panel in the user interface based on second display settings of the second panel, the second panel displaying at least a portion of the result of the second query; and in response to user input changing the displayed result in the first panel: re-execute the second query; and update the display of the second panel in the user interface based on results of the re-executed second query.
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
G06F 40/14 - Documents en configuration arborescente
A system is configured to provide a dashboard creation system. Panels associated with queries for retrieving information from a database are shown in a user interface. Various other user interfaces show query code, panel display settings, function code, dependencies, etc. Queries in a first query format access a data source. Queries in a second query format access a cache database that is synchronized with the data source.
G06F 40/143 - Balisage, p. ex. utilisation du langage SGML ou de définitions de type de document
G06F 3/0481 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect
G06F 16/172 - Mise en cache, pré-extraction ou accumulation de fichiers
G06F 16/178 - Techniques de synchronisation des fichiers dans les systèmes de fichiers
Methods, apparatuses and computer programs for manipulating data structures are provided. A method includes: receiving an indication of a target outcome, where the target outcome defines a transformation of a first dataset; providing to a first artificial intelligence model one or more requests to generate candidate functions; receiving, in response to the one or more requests, a plurality of distinct candidate functions from the first artificial intelligence model; providing, to a second artificial intelligence model, a request to generate the transformation on a first subset; receiving, from the second artificial intelligence model, an AI transformation of the first subset; executing each of the plurality of candidate functions on the first subset to generate a plurality of test; validating one or more of the candidate functions; and executing one of the validated candidate functions on the first dataset to achieve the transformation of the first dataset.
A system architecture can be used to facilitate communication among applications that are native and/or non-native to an application environment. The system architecture can include a first application environment executed on a client-side computing device. The first application environment can execute software applications that are native thereto. The first application environment can further execute software applications that are native thereto, but which software applications themselves comprise second application environments of types different from the first application environment, and which software applications can therefore execute additional software applications that are non-native to the first application environment. The first application environment can further execute a computation engine that is configured to store and execute instructions received from the first software application, the second software application, or both.
Methods and systems for structuring, storing and displaying time series data in a user interface. One system includes processors executing instructions to determine, from time series data from a first sensor, a first subset of time series data for the first batch from the first start time and the first end time, determine, from the time series data from the first sensor, a second subset of time series data for the second batch from the second start time and the second end time, generate a time series user interface comprising a chart, the chart including a first plot for the first subset of time series data and a second plot for the second subset of time series data, the first plot being aligned to the second plot, and cause presentation of the time series user interface.
G06F 11/32 - Surveillance du fonctionnement avec indication visuelle du fonctionnement de la machine
G06F 16/36 - Création d’outils sémantiques, p. ex. ontologie ou thésaurus
G06F 16/383 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
Systems and methods for dynamically generating application programming interfaces and managing functions associated with a data object type. In an aspect, the system accesses an object definition for a type of data object. The system generates an application programming interface associated with the type of data object, based at least partly on the object definition. The system determines a change to the object definition for the type of data object and updates the application programming interface based at least partly on the change to the object definition.
At least some embodiments of the present disclosure are related to methods and systems for evaluating, generating, and/or prototyping data pipelines. In certain embodiments, a system is configured to perform operations include: receiving an input dataset, the input dataset including a data schema; generating a first prompt based on the input dataset and a first prompt structure having one or more text strings and one or more blanks; providing the first prompt to a language model; receiving a use case generated by the language model for the input dataset, the use case including a description of how to use the input dataset; generating a data pipeline based on the use case; and applying the data pipeline to the input dataset to generate an output dataset.
A system may use a large language model (“LLM”) to generate a data pipeline. The system can receive a natural language query and a selection of a plurality of data sets for generating a data pipeline and generate a prompt comprising at least: the natural language query, indications of the plurality of data sets, an indication of a format of a first computer language, and an indication of available data transformations. The system can transmit the prompt to an LLM and receive, from the LLM, a response to the prompt in the format of the first computer language. The system can parse the response in the first computer language to identify at least an indication of one or more recommended data transformations. The system can generate, based on the indication of the one or more recommended data transformations, the data pipeline using a second computer language.
Devices, systems, and methods for generating summaries are disclosed. In some implementations, a method can include receiving a plurality of event logs, at least one event log of the plurality of event logs including unstructured data and a corresponding event time. In addition, the method can include generating a series of event logs according to event times of the plurality of event logs. The method can include receiving a time window of interest corresponding to one or more event logs in the generated series of event logs. Moreover, the method can include generating a text summary by applying a language model to unstructured data corresponding to the one or more event logs in the time window of interest. Also, the method can include transmitting the text summary to a computing device.
A method of determining and displaying metadata that represents provenance of columns in a data store comprises receiving query data expressed in a human-readable language and describing one or more transformations of data tables of a distributed database system or columns of the data tables; parsing the query data to create a data structure for unresolved transforms in which the data tables are not matched with the columns; based in part upon table schema metadata describing the columns of the data tables, creating an additional data structure for resolved transforms, the additional data structure matching the data tables with the columns and specifying inputs and outputs of each transformation of the one or more transformations; based on information in the additional data structure, creating and causing display of a visual graph of the columns of the data tables and relationships between the columns, relating to the one or more transformations.
G06F 16/26 - Exploration de données visuellesNavigation dans des données structurées
G06F 16/21 - Conception, administration ou maintenance des bases de données
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
Disclosed herein are systems and techniques for centralized data retention and deletion. Data can be ingested from multiple external data sources and saved internally for use to process data modification (e.g., deletion) requests via a data processing pipeline, which may apply eligibility checks and modification logic to determine the appropriate modifications to the relevant data items to comply with the data modification request. Various user interfaces may be generated to provide a user with oversight of the data processing pipeline and the data modifications. The user may review and trigger the modification of data stored at the external data sources and/or internally.
An example method of determining geolocations of objects based on information retrieved from heterogeneous data sources comprises: receiving, from a first data source associated with an object by an ontology-defined relationship, a first dataset including a first data item specifying a first time identifier and a first geolocation associated with the object; receiving, from a second data source associated with an object by an ontology-defined relationship, a second dataset including a second data item specifying a second time identifier and a second geolocation associated with the object; and determining, by applying a rule set associated with the ontology to the first dataset and the second dataset, a geolocation of the object and a corresponding time identifier.
G06F 16/338 - Présentation des résultats des requêtes
G06F 16/387 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
G06N 5/025 - Extraction de règles à partir de données
Systems and methods for data hydration are provided. In some examples, a method includes accessing a compiler. In some examples, the compiler is associated with a source graph, a domain graph, and a mapping profile. In some examples, the domain graph includes one or more domain data schemas. In some examples, the method further includes receiving a source dataset from a source system, and applying the compiler to the source dataset from the source system to generate a domain dataset. In some examples, the domain dataset uses at least one of the one or more domain data schemas. In some examples, the method is performed using one or more processors.
Computer-implemented systems and methods are disclosed that query collections of documents. Disclosed embodiments may include receiving, via a user interface, a first search query comprising a text string. Disclosed embodiments may include, responsive to receiving the first search query, initializing a first query object based on the text string. Further, disclosed embodiments may include translating the first query object to match the formatting of a search engine, the translated first query object capable of searching a plurality of collections of documents. Disclosed embodiments may also include receiving aggregated query results from a search engine based on the translated first query object. Some disclosed embodiments may include reformatting the aggregated query results based on respective configuration files of the collections. Additionally, disclosed embodiments may include rendering a graphical user interface that facilitates user interaction with the reformatted aggregate query results.
An apparatus, computer-implemented method and computer program are disclosed for synchronising dataset updates. For example, the method may comprise providing a first code branch associated with a plurality of code sets which, when executed, produce respective time-series datasets for provision to a downstream process linked to the first code branch. The method may also comprise generating a second code branch, based on the first code branch, the second code branch executing the plurality of code sets as part of an updating process and, if successful, storing respective time-series datasets to respective memory locations associated with the second code branch. Another part of the method may comprise determining if all code sets executed by the second code branch have successfully committed. Responsive to a positive determination, one or more pointers, e.g. all pointers, associated with the first code branch may be updated to point to the respective memory locations associated with the second code branch in order that the respective successfully-committed time-series datasets are provided to the downstream process.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
A system for managing a web application is disclosed. The system is programmed to enable graphically building a web application having one webpage with multiple views, where a view can have multiple sections and can contain a section from another view. The web application includes a hierarchical structure of nodes respectfully for generating the multiple views. Each node can be accessed separately and each node can reference certain other nodes.
Computing systems methods, and non-transitory storage media are provided for receiving a monitoring request. The monitoring request includes one or more entities or attributes to be monitored, one or more rules to be evaluated with respect to the entities or attributes, and one or more downstream actions to be selectively triggered based on the evaluation. Next, data regarding the entities or the attributes is obtained. Next, a log is generated. The log includes changes or updates, relative to a previous iteration, of the entities or the attributes. The changes or updates correspond to the rules. Next, the changes or the updates are evaluated against the one or more rules and based on the log. Next, one or more actions are selectively implemented based on the evaluation of the changes or the updates.
A computing system and methods are provided for georeferencing stabilization. An exemplary method includes: obtaining a video stream capturing an area from a camera of a drone, where the video stream includes a plurality of frames, each including a field of view of the image capturing device and metadata of the image capturing device when the frame is captured; constructing a geographic (geo) lattice for the field of view in each of the plurality of frames, the geo lattice comprises a plurality of points, each being associated with raw coordinates determined based on the corresponding metadata; and building a lattice map with stabilized geo coordinates by (1) aligning the frames, (2) averaging the raw geo coordinates for given intersection points, and (3) building the lattice map based on the averaged geo coordinates of the intersection points.
H04N 23/68 - Commande des caméras ou des modules de caméras pour une prise de vue stable de la scène, p. ex. en compensant les vibrations du boîtier de l'appareil photo
B64C 39/02 - Aéronefs non prévus ailleurs caractérisés par un emploi spécial
B64U 101/30 - Véhicules aériens sans pilote spécialement adaptés à des utilisations ou à des applications spécifiques à l’imagerie, à la photographie ou à la vidéographie
G06F 18/2413 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
G06T 7/35 - Détermination des paramètres de transformation pour l'alignement des images, c.-à-d. recalage des images utilisant des procédés statistiques
A computing system generates user interface data renderable to display an interactive graphical user interface including a cell-based grid having a first axis and a second axis. The first axis corresponds to one or more assets. The second axis corresponds to one or more time periods. The cell-based grid comprises a plurality of cells indicating values of the one or more assets for the one or more time periods. The interactive graphical user interface displays information relating to the value indicated in the selected cell responsive to a user selection.
Systems and methods are disclosed herein for reducing a risk of associating with a client that may engage in illegal activity. A system accesses data associated with an entity for a given context, applies a plurality of AI models to the data based on the context to generate a plurality of AI assessments. Data for showing risk factors, assessments of the risk factors, and data for evaluating risk factors can be transmitted for rendering in a user interface in a display device. Analyst feedback can be received and used to update the AI models.
Various systems and methods are provided that display various geographic maps and depth graphs in an interactive user interface in substantially real-time in response to input from a user in order to determine information related to measured data points, depth levels, and geological layers and provide the determined information to the user in the interactive user interface. For example, a computing device may be configured to retrieve data from one or more databases and generate one or more interactive user interfaces. The one or more interactive user interfaces may display the retrieved data in a geographic map, a heat map, a cross-plot graph, or one or more depth graphs. The user interface may be interactive in that a user may manipulate any of the graphs to identify trends or current or future issues.
G06F 3/04847 - Techniques d’interaction pour la commande des valeurs des paramètres, p. ex. interaction avec des règles ou des cadrans
G06F 3/04817 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] fondées sur des propriétés spécifiques de l’objet d’interaction affiché ou sur un environnement basé sur les métaphores, p. ex. interaction avec des éléments du bureau telles les fenêtres ou les icônes, ou avec l’aide d’un curseur changeant de comportement ou d’aspect utilisant des icônes
G06F 3/04842 - Sélection des objets affichés ou des éléments de texte affichés
G06F 16/29 - Bases de données d’informations géographiques
G06T 11/20 - Traçage à partir d'éléments de base, p. ex. de lignes ou de cercles
