A computer system is provided that allows participants to submit agent data structures for processing. Each agent data structure includes a valuation function for a first resource and a property of a second resource. The computer system performs a dual sided evaluation process to determine when contra-sided agents match with one another. A match is determined by comparing results of valuation functions of the agent data structures.
A first transaction computer system and a second transaction computer system are provided. The first transaction computer system receives data transaction requests that may be routed to the second transaction computer system. The second transaction computer system attempts to match the routed data transaction request against pending data transaction requests using hidden attributes.
G06Q 40/04 - TransactionsOpérations boursières, p. ex. actions, marchandises, produits dérivés ou change de devises
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande
3.
Display screen or portion thereof with animated graphical user interface
A distributed computing system is provided that communicates with a routing computer system. A routing module that is internal to the distributed computing system controls how and when data transaction requests are sent to the routing computer system for routing to destination systems.
H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande
H04L 67/1008 - Sélection du serveur pour la répartition de charge basée sur les paramètres des serveurs, p. ex. la mémoire disponible ou la charge de travail
H04L 67/5682 - Politiques ou règles de mise à jour, de suppression ou de remplacement des données stockées
5.
SYSTEMS AND METHODS OF CHAINED CONVERSATIONAL PROMPT ENGINEERING FOR INFORMATION RETRIEVAL
A system is provided for processing user queries by using an automated agent and a workflow. The system comprises reusable components that include states, tools, and/or data sources. Based on analysis of a query's content and goals, the system generates a workflow comprising a sequence of states, each state optimized for a subtask and dynamically bound to a selected tool(s) for that specific query. The workflow can provide a structured high-level control, while allowing for flexible selection of the tool(s) for each state of the workflow for that given query. The system produces a result using the structured workflow and selected tools, answering a user's original query.
G06V 30/412 - Analyse de mise en page de documents structurés avec des lignes imprimées ou des zones de saisie, p. ex. de formulaires ou de tableaux d’entreprise
G06V 30/413 - Classification de contenu, p. ex. de textes, de photographies ou de tableaux
6.
Display screen or portion thereof with animated graphical user interface
A data analysis computer system is provided that receives a timeseries dataset and generates implied data from the dataset. The dataset is further vectorized to reduce the dimensionality of the data. Users provide input to identify windows of data that either positively or negatively correlate to instances of a given type of occurrence within the data. The user defined windows are converted to fixed sized windows and a machine learning algorithm constructs a model from the data. The model is used to predict instances of the given type of occurrence in newly received data. Validation of the predications may be performed.
A computer system includes a transceiver that receives over a data communications network different types of input data from multiple source nodes and a processing system that defines for each of multiple data categories, a set of groups of data objects for the data category based on the different types of input data. Predictive machine learning model(s) predict a selection score for each group of data objects in the set of groups of data objects for the data category for a predetermined time period. Control machine learning model(s) determine how many data objects are permitted for each group of data objects based on the selection score. Decision-making machine learning model(s) prioritize the permitted data objects based on one or more predetermined priority criteria. Subsequent activities of the computer system are monitored to calculate performance metrics for each group of data objects and for data objects actually selected during the predetermined time period. Predictive machine learning model(s) and decision-making machine learning model(s) are adjusted based on the performance metrics to improve respective performance(s).
A system for processing distributed transactions is provided. The system includes a sequencer that communicates an atomic message stream to multiple different service instances. The service instances each process the messages from the message stream into a local queue. Each service instance also executes a state machine by reading messages from a queue and transitioning between states in the state machine while also performing one or more operations in connection with performing a distributed transaction.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
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
11.
DELAYED PROCESSING FOR ELECTRONIC DATA MESSAGES IN A DISTRIBUTED COMPUTER SYSTEM
A distributed computer system is provided. The distributed computer system includes at least one sequencer computing node and at least one matcher computing node. Electronic data messages are sequenced by the sequencer and sent to at least matcher computing node. The matcher computing node receives the electronic data messages and a reference value from an external computing source. New electronic data messages are put into a pending list before they can be acted upon by the matcher. A timer is started based on a comparison of the reference value (or a calculation based thereon) to at least one attribute or value of a new electronic data message. When the timer expires, the electronic data message is moved from the pending list to another list—where it is eligible to be matched against other, contra-side electronic data messages.
G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
G06Q 40/04 - TransactionsOpérations boursières, p. ex. actions, marchandises, produits dérivés ou change de devises
H04L 49/901 - Dispositions de mémoires tampon en utilisant un descripteur de stockage, p. ex. des pointeurs de lecture ou d'écriture
H04L 67/1029 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour accéder à un serveur parmi une pluralité de serveurs répliqués en utilisant des données liées à l'état des serveurs par un répartiteur de charge
12.
DATA PACKET PROCESSING METHODS, SYSTEMS, AND APPARATUS
A network capture device receives data packets received by one or more packet switches in a data communications network and processes each of the data packets decoding the data packet and determining whether the data packet is a financial data packet or not. The network capture device transmits, to a risk exposure computer system, the data packets determined to be financial data packets.
A computer system is provided and programmed to assemble a plurality of synthetic datasets and blend those synthetic datasets into a synthesized dataset. An evaluation is then performed to determine whether an existing model should be associated with the synthesized dataset or a new model should be trained from an existing model using the synthesized dataset.
The described technology relates to systems and techniques for accessing a database by dynamically choosing an index from a plurality of indexes that includes at least one learned index and at least one non-learned index. The availability of learned and non-learned indexes for accessing the same database provides for flexibility in accessing the database, and the dynamic selection between learned indexes and non-learned indexes provide for choosing the index based on the underlying data in the database and the characteristics of the query. Certain example embodiments provide a learned model that accepts a set of features associated with the query as input, and outputs a set of evaluated weights for respective features, which are then processed according to a set of rules to predict the most efficient index to be used.
A computer system is provided for monitoring and detecting changes in a data generating processes, which may be under a multi-dimensional and unsupervised setting. A target dataset is split into paired subgroups by a separator and one or more detectors are applied to detect changes, anomalies, inconsistencies, and the like between the paired subgroups. Metrics may be generated by the detector(s), which are then passed to an evaluating system.
A computer system is provided that is designed to handle multi-label classification. The computer system includes multiple processing instances that are arranged in a hierarchal manner and execute differently trained classification models. The classification task of one processing instance and the executed model therein may rely on the results of classification performed by another processing instance. Each of the models may be associated with a different threshold value that is used to binarize the probability output from the classification model.
G06F 18/241 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques
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”
The described technology provides a capability for web applications from different domains to interact within one application environment. For example, an enterprise web application executing on a client terminal is provided the capability to monitor a second web application from a third party vendor even when the second web application is independently executing within an iframe or the like within the enterprise web applications container or context. In some example embodiments, the communication is enabled by a composite cookie or key that incorporates portions of an enterprise web application cookie or key and also portions of a vendor web application cookie or key.
The described technology relates to a real-time processing of network packets. An example system relates to reordering messages received at a server over a communication network from distributed clients, in order to, among other things, eliminate or at least substantially reduce the effects of jitter (delay variance) experienced in the network. The reordering of messages may enable the example data processing application to improve the consistency of processing packets in the time order of when the respective packets entered a geographically distributed network.
H04L 47/283 - Commande de fluxCommande de la congestion par rapport à des considérations temporelles en réponse à des retards de traitement, p. ex. causés par une gigue ou un temps d'aller-retour [RTT]
H04L 47/56 - Ordonnancement des files d’attente en implémentant un ordonnancement selon le délai
H04L 47/62 - Ordonnancement des files d’attente caractérisé par des critères d’ordonnancement
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Providing online non-downloadable videos in the field of sports and business; Providing online interviews featuring sports figures in the field of sports and business for entertainment purposes; Entertainment services, namely, an ongoing series featuring business and sports provided through online streaming and websites; Educational and entertainment services, namely, a continuing program about sports figures accessible via computer networks
20.
BOARD PORTAL SUBSIDIARY MANAGEMENT SYSTEM, METHOD, AND COMPUTER PROGRAM PRODUCT
A board portal system provides the ability to manage multiple boards, where each of the boards may be a separate legal entity. The board portal may provide the ability to establish links between the multiple boards and create parent-child relationships with subsidiary boards. With the board portal, users can create content and make it viewable and accessible across multiple boards that related through a parent-child relationship. At the same time, the board portal maintains a requisite level of separation between the related boards in the portal using encryption and/or other separation techniques. As a result, the board portal facilitates flexible workflow patterns and communication processes based on the proper hierarchical structure that exists between the parent organization and its subsidiaries.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
The technology relates to systems and methods for transcribing audio of a meeting. Upon transcribing the audio, the systems and methods can parse different portions of the prescribed audio so that they may attribute the different portions to a particular speaker. These transcribed portions that are attributed to a particular speaker are made available for viewing and interacting using a graphical user interface.
G06F 16/683 - Recherche de données 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
G06F 16/638 - Présentation des résultats des requêtes
G06F 40/143 - Balisage, p. ex. utilisation du langage SGML ou de définitions de type de document
G10L 15/26 - Systèmes de synthèse de texte à partir de la parole
G10L 17/00 - Techniques d'identification ou de vérification du locuteur
22.
Systems and methods of chained conversational prompt engineering for information retrieval
A system is provided for processing user queries by using an automated agent and a workflow. The system comprises reusable components that include states, tools, and/or data sources. Based on analysis of a query's content and goals, the system generates a workflow comprising a sequence of states, each state optimized for a subtask and dynamically bound to a selected tool(s) for that specific query. The workflow can provide a structured high-level control, while allowing for flexible selection of the tool(s) for each state of the workflow for that given query. The system produces a result using the structured workflow and selected tools, answering a user's original query.
G06V 30/412 - Analyse de mise en page de documents structurés avec des lignes imprimées ou des zones de saisie, p. ex. de formulaires ou de tableaux d’entreprise
G06V 30/413 - Classification de contenu, p. ex. de textes, de photographies ou de tableaux
23.
Systems and methods of processing queries using multi-tool agents and modular workflows
A system is provided for processing user queries by using an automated agent and a workflow. The system comprises reusable components that include states, tools, and/or data sources. Based on analysis of a query's content and goals, the system generates a workflow comprising a sequence of states, each state optimized for a subtask and dynamically bound to a selected tool(s) for that specific query. The workflow can provide a structured high-level control, while allowing for flexible selection of the tool(s) for each state of the workflow for that given query. The system produces a result using the structured workflow and selected tools, answering a user's original query.
A sentiment analysis computing system includes a storage medium and a processing system. Sentiment input is received from audience members viewing a streamed/webcasted event. The received input is stored to the storage medium. A time slice of the webcasted event is determined and sentiment inputs that are within that time slice are obtained. A sentiment value is calculated for the determined time slice based on aggregated sentiment values. The calculated sentiment value for the time slice is then output by the sentiment analysis computing system.
Systems and methods that provide improved (e.g., higher accuracy and time-efficient) aggregation of report data are described. Example embodiments effectively combine machine learning and deep learning in a processing pipeline to classify unlabeled source data to determine a reliable classification, or a labeling, of that source data. The classified or labeled source data can be used to generate reports that provide extensive insight into the aggregated source data.
An electronic resource tracking and storage computer system is provided that communicates with a distributed blockchain computing system that includes multiple computing nodes. The system includes a storage system, a transceiver, and a processing system. The storage system includes an resource repository and transaction repository that stores submitted blockchain transactions. A new resource issuance request is received, and a new resource is added to the resource repository in response. A new blockchain transaction is generated and published to the blockchain. In correspondence with publishing to the blockchain, the transaction storage is updated with information that makes up the blockchain transaction and some information that was not included as part of the blockchain transaction. The transaction storage is updated when the blockchain is determined to have validated the previously submitted blockchain transaction.
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
G06F 16/21 - Conception, administration ou maintenance des bases de données
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 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
G06N 5/022 - Ingénierie de la connaissanceAcquisition de la connaissance
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06F 18/2113 - Sélection du sous-ensemble de caractéristiques le plus significatif en classant ou en filtrant l'ensemble des caractéristiques, p. ex. en utilisant une mesure de la variance ou de la corrélation croisée des caractéristiques
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
G06N 5/01 - Techniques de recherche dynamiqueHeuristiquesArbres dynamiquesSéparation et évaluation
36 - Services financiers, assurances et affaires immobilières
Produits et services
Providing and updating a financial index; Providing financial indices based on selected groups of securities; Collection and compilation of information into computer databases in the field of financial indices; Economic forecasting services; Providing business information in the field of financial indices, exchange-traded funds (ETFs), exchange-traded products (ETPs), futures, and options; Compilation of statistics; Compiling and analyzing statistics, data and other sources of information for business purposes; Business data analysis; Providing a financial index in the nature of quantitative measurements for analyzing investor attitudes; Providing and updating a financial index of securities values and classification, analysis, and reporting thereof; Providing a financial index in the nature of quantitative measurements for analyzing the performance of energy limited partnerships; Providing financial indices of select securities to enable consumers to evaluate investments and market trends in the securities market; Providing financial indices of select bonds to enable consumers to evaluate investments and market trends in the bond market; Providing business information in the field of business; Compiling financial, securities, stock exchange, trade and quote, index value and other financial market information for business purposes; Providing information and news in the field of business; Analyzing and compiling business data for creating indices concerning securities trading, interests, prices, exchange rates and other economic data concerning securities Financial information provided by electronic means; Providing financial information via a web site; Financial information provided by electronic means in the field of financial data; Financial analysis; Financial information provided by electronic means in the field of securities pricing, equities pricing, credit pricing, credit market pricing, financial instrument price discrepancy, price discrepancy, and financial instrument prices; Stock exchange quotations; Stock exchange price quotations; Stock exchange quotation and listing services; Provision of financial information relating to the finance industry involved in environmentally focused investments; Financial administration of stock exchange trading of shares and other financial securities in financial markets; Organization of stock exchanges for the benefit of the trade of stocks and other financial values; Providing an on-line computer database in the field of stock/securities market information; Financial information provided by electronic means in the field of financial management and financial asset management; Financial information provided by electronic means in the field of financial indices, exchange-traded funds (ETFs), exchange-traded products (ETPs), futures, and options
36 - Services financiers, assurances et affaires immobilières
Produits et services
Providing and updating a financial index; Providing financial indices based on selected groups of securities; Collection and compilation of information into computer databases in the field of financial indices; Economic forecasting services; Providing business information in the field of financial indices, exchange-traded funds (ETFs), exchange-traded products (ETPs), futures, and options; Compilation of statistics; Compiling and analyzing statistics, data and other sources of information for business purposes; Business data analysis; Providing a financial index in the nature of quantitative measurements for analyzing investor attitudes; Providing and updating a financial index of securities values and classification, analysis, and reporting thereof; Providing a financial index in the nature of quantitative measurements for analyzing the performance of energy limited partnerships; Providing financial indices of select securities to enable consumers to evaluate investments and market trends in the securities market; Providing financial indices of select bonds to enable consumers to evaluate investments and market trends in the bond market; Providing business information in the field of business; Compiling financial, securities, stock exchange, trade and quote, index value and other financial market information for business purposes; Providing information and news in the field of business; Analyzing and compiling business data for creating indices concerning securities trading, interests, prices, exchange rates and other economic data concerning securities Financial information provided by electronic means; Providing financial information via a web site; Financial information provided by electronic means in the field of financial data; Financial analysis; Financial information provided by electronic means in the field of securities pricing, equities pricing, credit pricing, credit market pricing, financial instrument price discrepancy, price discrepancy, and financial instrument prices; Stock exchange quotations; Stock exchange price quotations; Stock exchange quotation and listing services; Provision of financial information relating to the finance industry involved in environmentally focused investments; Financial administration of stock exchange trading of shares and other financial securities in financial markets; Organization of stock exchanges for the benefit of the trade of stocks and other financial values; Providing an on-line computer database in the field of stock/securities market information; Financial information provided by electronic means in the field of financial management and financial asset management; Financial information provided by electronic means in the field of financial indices, exchange-traded funds (ETFs), exchange-traded products (ETPs), futures, and options
36 - Services financiers, assurances et affaires immobilières
Produits et services
Providing and updating a financial index; Providing financial indices based on selected groups of securities; Collection and compilation of information into computer databases in the field of financial indices; Economic forecasting services; Providing business information in the field of financial indices, exchange-traded funds (ETFs), exchange-traded products (ETPs), futures, and options; Compilation of statistics; Compiling and analyzing statistics, data and other sources of information for business purposes; Business data analysis; Providing a financial index in the nature of quantitative measurements for analyzing investor attitudes; Providing and updating a financial index of securities values and classification, analysis, and reporting thereof; Providing a financial index in the nature of quantitative measurements for analyzing the performance of energy limited partnerships; Providing financial indices of select securities to enable consumers to evaluate investments and market trends in the securities market; Providing financial indices of select bonds to enable consumers to evaluate investments and market trends in the bond market; Providing business information in the field of business; Compiling financial, securities, stock exchange, trade and quote, index value and other financial market information for business purposes; Providing information and news in the field of business; Analyzing and compiling business data for creating indices concerning securities trading, interests, prices, exchange rates and other economic data concerning securities Financial information provided by electronic means; Providing financial information via a web site; Financial information provided by electronic means in the field of financial data; Financial analysis; Financial information provided by electronic means in the field of securities pricing, equities pricing, credit pricing, credit market pricing, financial instrument price discrepancy, price discrepancy, and financial instrument prices; Stock exchange quotations; Stock exchange price quotations; Stock exchange quotation and listing services; Provision of financial information relating to the finance industry involved in environmentally focused investments; Financial administration of stock exchange trading of shares and other financial securities in financial markets; Organization of stock exchanges for the benefit of the trade of stocks and other financial values; Providing an on-line computer database in the field of stock/securities market information; Financial information provided by electronic means in the field of financial management and financial asset management; Financial information provided by electronic means in the field of financial indices, exchange-traded funds (ETFs), exchange-traded products (ETPs), futures, and options
31.
SYSTEMS AND METHODS TO REPLICATE PRIVATE KEY SHARES FROM MULTI-PARTY COMPUTATION (MPC) NODES IN A PRIMARY SUBSYSTEM TO MPC NODES A BACKUP SUBSYSTEM
A system includes a primary asset custody subsystem in a first cloud computing data center and a backup asset custody subsystem in a second cloud computing data center different from the first cloud computing data center. The primary subsystem includes a plurality of primary multi-party computation (MPC) clusters, where each primary MPC cluster is allocated to an asset owner and includes a primary MPC client and a plurality of primary MPC nodes. The backup subsystem includes a plurality of backup MPC clusters corresponding to the plurality of primary MPC clusters, where each backup MPC cluster is allocated to the asset owner of its corresponding primary MPC cluster and includes a backup MPC client and a plurality of backup MPC nodes. The backup MPC client sends an export public key from each backup MPC node to the primary MPC client, where each export public key is part of a corresponding export public key-export private key pair. The primary MPC client sends each export public key to a corresponding primary MPC node, and in response, receives from each primary MPC node a corresponding encrypted private key share encrypted with a corresponding export public key. The primary MPC client then sends the encrypted private key shares to the backup MPC client, which transmits the encrypted private key shares to corresponding backup MPC nodes. Each backup MPC node decrypts a corresponding encrypted private key share using the export private key from the corresponding export public key-export private key pair to obtain a corresponding backup private key share which can be used if the backup subsystem takes over operation, and to store the decrypted corresponding backup private key share.
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
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
32.
SYSTEMS, METHODS, AND COMPUTER-READABLE MEDIA FOR DATA SECURITY
Systems and methods are provided for data security. A server system provides data security using one or more processor devices, one or more communication interfaces, and one or more memory devices including computer-executable instructions. Those instructions cause the one or more processor devices to: monitor one or more requests or activities of a computing device; compare the monitored one or more requests or activities with a database of predetermined characteristics to determine whether the monitored one or more requests or activities indicates that the computing device downloaded or attempted to download more than a threshold number of data files or objects; and determine that the one or more requests or activities is suspicious when the comparing determines that the one or more requests or activities indicates that the computing device downloaded or attempted to download more than the threshold number of data files or objects, which causes a response to hinder the monitored one or more requests or activities.
A distributed computing system is provided that communicates with a routing computer system. A routing module that is internal to the distributed computing system controls how and when data transaction requests are sent to the routing computer system for routing to destination systems.
H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande
H04L 67/1008 - Sélection du serveur pour la répartition de charge basée sur les paramètres des serveurs, p. ex. la mémoire disponible ou la charge de travail
H04L 67/5682 - Politiques ou règles de mise à jour, de suppression ou de remplacement des données stockées
34.
SYSTEMS AND METHODS OF ROUTING DATA TRANSACTION MESSAGES FOR DISTRIBUTED SYSTEMS
A distributed computing system is provided that communicates with a routing computer system. A routing module that is internal to the distributed computing system controls how and when data transaction requests are sent to the routing computer system for routing to destination systems.
A distributed computing system is provided that communicates with a routing computer system. A routing module that is internal to the distributed computing system controls how and when data transaction requests are sent to the routing computer system for routing to destination systems.
Natural language processing techniques provide sentence level analysis on one or more topics that are associated with keywords. Indirect learning is used to expand the understanding of the keywords and associated topics. Semantic similarity is used on a sentence-level to assess whether a given sentence relates or mentions a particular topic. In some examples, additional keywords are suggested using filtering techniques in connection with graph embedding-based entity linking techniques.
An information computer system is provided for securely releasing time-sensitive information to recipients via a blockchain. A submitter submits a document to the system and a blockchain transaction is generated and submitted to the blockchain based on the document (e.g., the document is included as part of the blockchain transaction). An editor may edit the document and an approver may approve the document for release to the recipients. Each modification and/or approval of the document is recorded as a separate transaction on the blockchain where each of the submitter, editor, approver, and recipients interact with the blockchain with corresponding unique digital identifiers—such as private keys.
G06F 21/64 - Protection de l’intégrité des données, p. ex. par sommes de contrôle, certificats ou signatures
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/06 - Circuits privés de paiement, p. ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
38.
SYSTEMS AND METHODS OF TRAINING NEURAL NETWORKS USING MACHINE LEARNING
A system that trains a neural network to generate an embedding is provided. The system uses the trained neural network to then train additional task models from the generated embeddings. The resulting trained models may then be deployed to distributed processing systems that accept and process data transaction requests. The models are used to provide predictions using the current state of a data structure, which is being continually modified based on newly received data transaction requests.
A system that trains a neural network to generate an embedding is provided. The system uses the trained neural network to then train additional task models from the generated embeddings. The resulting trained models may then be deployed to distributed processing systems that accept and process data transaction requests. The models are used to provide predictions using the current state of a data structure, which is being continually modified based on newly received data transaction requests.
H04L 41/16 - Dispositions pour la maintenance, l’administration ou la gestion des réseaux de commutation de données, p. ex. des réseaux de commutation de paquets en utilisant l'apprentissage automatique ou l'intelligence artificielle
G06N 20/20 - Techniques d’ensemble en apprentissage automatique
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
G06N 99/00 - Matière non prévue dans les autres groupes de la présente sous-classe
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
40.
Systems and methods to dynamically provision multi-party computation (MPC) nodes
A digital asset custody system dynamically provisions clusters of multi-party computation (MPC) nodes to securely create different private key shares for signing digital asset transactions and generate blockchain addresses for digital asset owners (AOs). Each cluster of MPC nodes is configured for an AO and to operate in a plurality of computing environments. Each of the computing environments is associated with a respective different signing party, and each computing environment includes a respective one of plural MPC node initializers and a respective one of plural MPC node operators. An MPC controller and MPC node initializers perform operations to generate first configuration information for each MPC node in a first MPC cluster of MPC nodes. Each MPC node operator, based on the first configuration information, deploys one of the MPC nodes in the first MPC cluster in the computing environment corresponding to where the MPC node operator operates, such that the one MPC node in the first MPC cluster is deployed into a different one of the plurality of computing environments as compared to the computing environments into which the other MPC nodes in the first MPC cluster are deployed. Analogous operations are performed to generate second configuration information to deploy a second MPC cluster, third configuration information to deploy a third MPC cluster, etc. as desired.
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
41.
SYSTEMS AND METHODS FOR CALENDAR SYNCHRONIZATION WITH ENTERPRISE WEB APPLICATIONS
The described technology relates to integrating events electronically scheduled in enterprise web applications and other event management applications. An improved capability is provided for an event management application like, for example, Microsoft's Outlook™ to provide the user with additional useful information and/or resources associated with scheduled events such as, but not limited to, meetings. Improved capabilities are provided to the enterprise web application clients based upon integration with event applications such as Outlook. Embodiments use a unique identifier generated for an event scheduled in one application for associating corresponding event information in the second application, such that the scheduled event calendars in the first and second applications can be synchronized without duplicating the event information between the two applications.
A computer system is provided that includes a paired list of data transaction requests on which a matching process is performed. There are multiple different types of data transaction requests that are stored in the paired list including data transaction requests with midpoint attributes and data transaction requests with discretion attributes. The computer system may determine how the multiple different types of data transaction requests may be match against each other. Two matching processes can be used to determine if a match exists between the first and second sides of the paired list. Matches that are determined at private values are not disseminated to third-parties via public market data feeds.
Example implementations of this disclosure relate to establishing and maintaining connections among data items that may be used for various reporting and/or display purposes. Connected data items may be differently named and may be in the same or different data collections. User interfaces are provided so that for a particular response data item, its associated other response data items can be found, viewed and operated upon by administrative users and/or client users efficiently in order to ensure consistency of the response data across multiple target output reports. Example implementations also include techniques implemented in front end systems and/or backend systems for efficiently searching for connectable data items, and to efficiently store and maintain the data items and their connections.
An electronic exchange computing system is provided that includes a computer storage system, at least one transceiver, and a processing system. The storage system stores an electronic order book. The transceiver receives data transaction requests and transmits messages of an electronic data feed. The processing system generates an identifier, which may be referred to as a transaction identifier, for received data transaction requests. The identifier may be generated in a non-sequential and increasing manner such that it is greater than previously generated identifiers. The processing system will process the data transaction request and generate an electronic data feed message based on how data transaction request is handled. The electronic data feed message is sent to client computing system and includes the generated identifier.
A system for providing a virtual data room for conducting due diligence on a plurality of documents that are remotely located and accessible over a computer network by a plurality of users using client computer systems. Documents are retrieved from the remote system and presented to a user on their local computing system for review and conducting due diligence tasks thereon. Based on the interaction the user has with the displayed document, due diligence status values that are associated with the display document are updated and stored with the virtual data room system. A display request is received and based on the request a display characteristic is calculated for a folder that includes a set of documents. The display characteristic is determined based on the due diligence status values of all of the documents within the folder.
G06F 16/16 - Opérations sur les fichiers ou les dossiers, p. ex. détails des interfaces utilisateur spécialement adaptées aux systèmes de fichiers
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
G06F 40/14 - Documents en configuration arborescente
46.
SYSTEMS AND METHODS FOR CALENDAR SHARING BY ENTERPRISE WEB APPLICATIONS
The described technology relates to integrating events electronically scheduled in enterprise web applications and other event applications. A capability is provided for events created by an enterprise web application and events from other external event streams to be presented in a consolidated calendar in the enterprise web application. Capabilities are also provided for sharing the calendar among enterprise users and non-enterprise users, and for efficiently generating the shared calendar.
An electronic exchange computing system is provided that includes a computer storage system, at least one transceiver, and a processing system. The storage system stores an electronic order book. The transceiver receives data transaction requests and transmits messages of an electronic data feed. The processing system determines that a first order has priority and generates a new order ID for the first order. The first order is maintained in the electronic order book (e.g., with a quantity of 0). Additional order instructions are received from a client computer system and are associated with the first order. A match is found based on the additional order instructions. A data feed update message is generated and transmitted as part of a real-time data feed and includes the newly generated order ID for the first order.
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
36 - Services financiers, assurances et affaires immobilières
38 - Services de télécommunications
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Providing financial information. Electronic message transmission; electronic data
transmission; transmission and delivery of financial data
via the internet. Software as a service (SaaS) services featuring software for
analyzing information in a database in the field of
financial services; software as a service (SaaS) services
featuring software for performing research in the field of
financial services.
49.
Systems and methods for generating datasets for model retraining
A computer system is provided and programmed to assemble a plurality of synthetic datasets and blend those synthetic datasets into a synthesized dataset. An evaluation is then performed to determine whether an existing model should be associated with the synthesized dataset or a new model should be trained from an existing model using the synthesized dataset.
Systems and methods that provide for executing a machine learning model in lockstep with a real-time transaction processing system are described. An example system includes a feature store in a memory, processes storing real-time data, including a clock signal, in designated memory regions in the feature store, and processes controlling the execution of the machine learning model in accordance with the clock signal.
Systems and methods that provide for executing a machine learning model in lockstep with a real-time transaction processing system are described. An example system includes a feature store in a memory, processes storing real-time data, including a clock signal, in designated memory regions in the feature store, and processes controlling the execution of the machine learning model in accordance with the clock signal.
A board portal system provides the ability to manage multiple boards, where each of the boards may be a separate legal entity. The board portal may provide the ability to establish links between the multiple boards and create parent-child relationships with subsidiary boards. With the board portal, users can create content and make it viewable and accessible across multiple boards that related through a parent-child relationship. At the same time, the board portal maintains a requisite level of separation between the related boards in the portal using encryption and/or other separation techniques. As a result, the board portal facilitates flexible workflow patterns and communication processes based on the proper hierarchical structure that exists between the parent organization and its subsidiaries.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
53.
WEBCAST SYSTEMS AND METHODS WITH AUDIENCE SENTIMENT FEEDBACK AND ANALYSIS
A sentiment analysis computing system includes a storage medium and a processing system. Sentiment input is received from audience members viewing a streamed/webcasted event. The received input is stored to the storage medium. A time slice of the webcasted event is determined and sentiment inputs that are within that time slice are obtained. A sentiment value is calculated for the determined time slice based on aggregated sentiment values. The calculated sentiment value for the time slice is then output by the sentiment analysis computing system.
Systems and methods are provided for recording ownership information in a distributed ledger (such as a blockchain), and for performing application processing utilizing the distributed ledger. An example server computer system is configured to: record on a blockchain ownership information of an asset; to configure, for each owner of the asset, a digital wallet associated with a private cryptographic key and at least one blockchain address; using a blockchain address from a digital wallet to access ownership information in the blockchain; perform application processing using the accessed ownership information; and record in the blockchain, updated ownership information or other information associated with the ownership information in accordance with the performed application processing.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 40/04 - TransactionsOpérations boursières, p. ex. actions, marchandises, produits dérivés ou change de devises
55.
COMPUTER-IMPLEMENTED SYSTEMS AND METHODS FOR INTELLIGENTLY RETRIEVING, ANALYZING, AND SYNTHESIZING DATA FROM DATABASES
A computer extracts from contact records that each include a contact identifier, a group identifier for each group with which the contact has had an interaction, and interaction information that indicates a number of interactions and a timing of a most recent interaction. The contact data records are processed to generate a contact profile record for each contact including group metric values and a corresponding value for each group metric value based on an interaction history of groups the contact has interacted with. An interaction analytics databases stores a set of contact profile records and group profile records for groups that include metric values associated with the group and an interaction history. They are processed with at least thousands of the contact profile records to determine group-contact compatibility factors. A compatibility parameter is generated and communicated for each of at least thousands of contacts based on the group-contact compatibility parameters.
Systems and methods that provide improved (e.g., higher accuracy and time-efficient) aggregation of report data are described. Example embodiments effectively combine machine learning and deep learning in a processing pipeline to classify unlabeled source data to determine a reliable classification, or a labeling, of that source data. The classified or labeled source data can be used to generate reports that provide extensive insight into the aggregated source data.
The described technology relates to a logging framework wherein identifiers are associated with various elements within a web application, such as pages within the application and portions of pages within the application. Additional identifiers may be associated with sessions within the application, instances of page visits within the application, and other facets of the application and user interactions with the application. The identifiers can be used to generate a log that indicates, among other information, a history of interactions performed by a user navigating the application.
A computer system is provided that includes a storage system, at least one transceiver, and a processing system with at least one hardware processor. The storage system stores a first list pair. The transceiver receives electronic data messages that each include a respective data transaction request. The processing system determines how the new data transaction request should be processed based on which communication protocol was used to submit the request. Updates regarding the first list pair are sent out to non-party client computer systems using different communication protocols, where one is faster than the other, but the slower update includes private data therein.
The described technology relates to developing and/or maintaining dashboards in enterprise web applications. In some aspects, a portal web application is configured to provide a user interface on a client device to create or modify a dashboard which includes a first plurality of widgets. A second plurality of widgets includes widgets published to the portal web application from a plurality of subscriber web applications, where each of the second plurality of widgets is used in at least one of said subscriber web applications, and the first plurality of widgets includes one or more widgets from the second plurality of widgets. In some other aspects, a dashboard management service is provided by which respective enterprise web applications can create and host widgets while sharing the same with other enterprise web applications which use dashboards developed using the dashboard management service.
36 - Services financiers, assurances et affaires immobilières
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Electronic message transmission; electronic data transmission; transmission and delivery of financial data via the internet Providing financial information Software as a service (SAAS) services featuring software for analyzing information in a database in the field of financial services; software as a service (SAAS) services featuring software for performing research in the field of financial services
61.
Systems and methods of optimizing resource allocation using machine learning and predictive control
A computer system includes a transceiver that receives over a data communications network different types of input data from multiple source nodes and a processing system that defines for each of multiple data categories, a set of groups of data objects for the data category based on the different types of input data. Predictive machine learning model(s) predict a selection score for each group of data objects in the set of groups of data objects for the data category for a predetermined time period. Control machine learning model(s) determine how many data objects are permitted for each group of data objects based on the selection score. Decision-making machine learning model(s) prioritize the permitted data objects based on one or more predetermined priority criteria. Subsequent activities of the computer system are monitored to calculate performance metrics for each group of data objects and for data objects actually selected during the predetermined time period. Predictive machine learning model(s) and decision-making machine learning model(s) are adjusted based on the performance metrics to improve respective performance(s).
A first transaction computer system and a second transaction computer system are provided. The first transaction computer system receives data transaction requests that may be routed to the second transaction computer system. The second transaction computer system attempts to match the routed data transaction request against pending data transaction requests using hidden attributes.
H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
63.
SYSTEMS AND METHODS OF OPTIMIZING RESOURCE ALLOCATION USING MACHINE LEARNING AND PREDICTIVE CONTROL
A computer system includes a transceiver that receives over a data communications network different input data sets from one or more source computers communicating with the data communications network, where an input data set includes data objects, each data object including associated data object attributes. A processing system processes the input data sets using a predictive machine learning model to predict for a predetermined time period a list of predicted object attribute values for data objects in the input data sets. The list of predicted object attribute values is sorted to generate a current, ranked list of data objects with predicted data object attribute values, which may be modified to account for a prior ranking of data objects. A subset of lower ranked data objects from the prior ranking of data objects is replaced with a subset of higher ranked data objects from the modified, ranked list of data objects with predicted object attribute values to generate a new ranking of data objects. Performance metric(s) for data objects are calculated for data objects in the new ranking of data objects relative to benchmark data for the data objects in the new ranking of data. The predictive machine learning model may be retrained based on the performance metric(s) to improve its performance.
Dynamic timers are determined using machine learning. The timers are used to control the amount of time that new data transaction requests wait before being processed by a data transaction processing system. The timers are adjusted based on changing conditions within the data transaction processing system. The dynamic timers may be determined using machine learning inference based on feature values calculated as a result of the changing conditions.
Dynamic timers are determined using machine learning. The timers are used to control the amount of time that new data transaction requests wait before being processed by a data transaction processing system. The timers are adjusted based on changing conditions within the data transaction processing system. The dynamic timers may be determined using machine learning inference based on feature values calculated as a result of the changing conditions.
Dynamic timers are determined using machine learning. The timers are used to control the amount of time that new data transaction requests wait before being processed by a data transaction processing system. The timers are adjusted based on changing conditions within the data transaction processing system. The dynamic timers may be determined using machine learning inference based on feature values calculated as a result of the changing conditions.
The described technology provides a capability to perform in-session updates to entitlements associated with a user's access to content served by a web application. The content may be from one or more external servers. The technology provides for automatically detecting changes to entitlements, and without requiring a user of an active session to initiate a new session, updating entitlement data in a memory such that subsequent requests for data made by the client in the same active session are serviced using the updated entitlements.
In some embodiments a distributed computing system is provided that includes a plurality of different feature modules and a matching engine. The different feature modules each provide different processing for handling parent requests and submitting, to the matching engine, commands for child data transaction requests that are associated with the parent request.
Dynamic timers are determined using machine learning. The timers are used to control the amount of time that new data transaction requests wait before being processed by a data transaction processing system. The timers are adjusted based on changing conditions within the data transaction processing system. The dynamic timers may be determined using machine learning inference based on feature values calculated as a result of the changing conditions.
G06F 9/46 - Dispositions pour la multiprogrammation
G06F 5/06 - Procédés ou dispositions pour la conversion de données, sans modification de l'ordre ou du contenu des données maniées pour modifier la vitesse de débit des données, c.-à-d. régularisation de la vitesse
70.
SYSTEMS AND METHODS OF DETERMINING DYNAMIC TIMERS USING MACHINE LEARNING
Dynamic timers are determined using machine learning. The timers are used to control the amount of time that new data transaction requests wait before being processed by a data transaction processing system. The timers are adjusted based on changing conditions within the data transaction processing system. The dynamic timers may be determined using machine learning inference based on feature values calculated as a result of the changing conditions.
A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.
G06N 5/022 - Ingénierie de la connaissanceAcquisition de la connaissance
G06F 16/25 - Systèmes d’intégration ou d’interfaçage impliquant les systèmes de gestion de bases de données
G06F 18/2113 - Sélection du sous-ensemble de caractéristiques le plus significatif en classant ou en filtrant l'ensemble des caractéristiques, p. ex. en utilisant une mesure de la variance ou de la corrélation croisée des caractéristiques
G06F 18/214 - Génération de motifs d'entraînementProcédés de Bootstrapping, p. ex. ”bagging” ou ”boosting”
G06N 5/01 - Techniques de recherche dynamiqueHeuristiquesArbres dynamiquesSéparation et évaluation
A distributed computing system is provided that communicates with a routing computer system. A routing module that is internal to the distributed computing system controls how and when data transaction requests are sent to the routing computer system for routing to destination systems.
H04L 47/125 - Prévention de la congestionRécupération de la congestion en équilibrant la charge, p. ex. par ingénierie de trafic
H04L 67/63 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises en acheminant une demande de service en fonction du contenu ou du contexte de la demande
74.
Matching techniques for data transaction requests with private attributes
A computer system is provided that includes a paired list of data transaction requests on which a matching process is performed. There are multiple different types of data transaction requests that are stored in the paired list including data transaction requests with midpoint attributes and data transaction requests with discretion attributes. The computer system may determine how the multiple different types of data transaction requests may be match against each other. Two matching processes can be used to determine if a match exists between the first and second sides of the paired list. Matches that are determined at private values are not disseminated to third-parties via public market data feeds.
A social intelligence system is presented that streams information from a source, queues the streamed information, analyzes/scores the queued data, and stores the analyzed/scored data in an analysis database. The analyzed/scored data can then be retrieved from the database for post-processing and stored in a client specific database for further reporting. By streaming the data into various message queues and scoring the data before storing in the analysis database, large volumes of data can be efficiently processed and analyzed for a particular person and/or entity.
G06F 16/2457 - Traitement des requêtes avec adaptation aux besoins de l’utilisateur
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
G06Q 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
H04L 51/52 - Messagerie d'utilisateur à utilisateur dans des réseaux à commutation de paquets, transmise selon des protocoles de stockage et de retransmission ou en temps réel, p. ex. courriel pour la prise en charge des services des réseaux sociaux
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
76.
Systems and methods for monitoring cross-domain applications in web environments
The described technology provides a capability for web applications from different domains to interact within one application environment. For example, an enterprise web application executing on a client terminal is provided the capability to monitor a second web application from a third party vendor even when the second web application is independently executing within an iframe or the like within the enterprise web applications container or context. In some example embodiments, the communication is enabled by a composite cookie or key that incorporates portions of an enterprise web application cookie or key and also portions of a vendor web application cookie or key.
The technology detects undesirable data packets. Data packets are received from multiple sources at one or more packet switches in a data communications network. The one or more packet switches route the data packets to one or more intended destination computing nodes and also transmit a copy of all the data packets received in the data communications network to a network capture device. The network capture device processes the data packets, detects financial data packets, and transmits the detected financial data packets for analysis by a risk exposure computer system that performs automatic financial risk analysis based on the detected financial data packets.
A computer system is provided for monitoring and detecting changes in a data generating processes, which may be under a multi-dimensional and unsupervised setting. A target dataset is split into paired subgroups by a separator and one or more detectors are applied to detect changes, anomalies, inconsistencies, and the like between the paired subgroups. Metrics may be generated by the detector(s), which are then passed to an evaluating system.
An electronic resource tracking and storage computer system is provided that communicates with a distributed blockchain computing system that includes multiple computing nodes. The system includes a storage system, a transceiver, and a processing system. The storage system includes an resource repository and transaction repository that stores submitted blockchain transactions. A new resource issuance request is received, and a new resource is added to the resource repository in response. A new blockchain transaction is generated and published to the blockchain. In correspondence with publishing to the blockchain, the transaction storage is updated with information that makes up the blockchain transaction and some information that was not included as part of the blockchain transaction. The transaction storage is updated when the blockchain is determined to have validated the previously submitted blockchain transaction.
H04L 29/00 - Dispositions, appareils, circuits ou systèmes non couverts par un seul des groupes
G06F 16/21 - Conception, administration ou maintenance des bases de données
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
A system is presented that profiles authors and social media data across different media platforms and is capable of determining the author's overall social impact. In one aspect, this is accomplished by using a data retrieval service to trawl various web-sites and social media platforms for information about authors which can then be associated with those authors in a profile database. In one example, an author may post an entry on his/her blog and the data retrieval service can access the profile information of the author, on the blog, where various aspects of the profile information (e.g., real name, employee information, home address) can be matched with candidates in a profile database. From the information gathered, authors can be linked across multiple, different platforms, and an overall social impact of each of the authors can be determined.
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
H04W 4/21 - Signalisation de servicesSignalisation de données auxiliaires, c.-à-d. transmission de données par un canal non destiné au trafic pour applications de réseaux sociaux
G06F 16/951 - IndexationTechniques d’exploration du Web
G06F 16/9535 - Adaptation de la recherche basée sur les profils des utilisateurs et la personnalisation
The described technology relates to a software application architecture allowing for creation of a web application that has multiple Single Page Applications (SPAs) within the application. The software application architecture includes components that are common to each page of the web application while also having components that are dynamically loaded to cater to specific respective pages within the application. The dynamically loadable components can be identified based on an identifier in a path being browsed using a web browser application. The described application architecture may be used in the context of AngularJS, as well as other SPA technologies and non-SPA technologies.
H04L 67/1021 - Sélection du serveur pour la répartition de charge basée sur la localisation du client ou du serveur
H04L 61/4511 - Répertoires de réseauCorrespondance nom-adresse en utilisant des répertoires normalisésRépertoires de réseauCorrespondance nom-adresse en utilisant des protocoles normalisés d'accès aux répertoires en utilisant le système de noms de domaine [DNS]
H04L 61/5007 - Adresses de protocole Internet [IP]
H04L 67/00 - Dispositions ou protocoles de réseau pour la prise en charge de services ou d'applications réseau
H04L 67/02 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP]
H04L 67/52 - Services réseau spécialement adaptés à l'emplacement du terminal utilisateur
H04L 67/60 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises
H04L 69/22 - Analyse syntaxique ou évaluation d’en-têtes
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software for sharing information
related to corporate board meetings; downloadable computer
software for sharing information related to business
meetings; downloadable computer software for sharing
information related to corporate governance; downloadable
computer software for providing corporate board access to
data related to corporate governance. Software as a service (SAAS) services featuring software for
sharing information related to corporate board meetings;
software as a service (SAAS) services featuring software for
sharing information related to business meetings; software
as a service (SAAS) services featuring software for sharing
information related to corporate governance; software as a
service (SAAS) services featuring software for providing
corporate board access to data related to corporate
governance.
84.
Client Device Information for Controlling Access to Web Applications
The described technology provides for plural application processes including at least one application in a browser to reliably acquire device information that can be used by other processes to accurately determine whether the plural applications are running on the same client device and/or are associated with aspects of the same client device. The more reliable determination of the devices associated with respective application processes can be used for various purposes such as, for example, user access management capabilities such as improved single sign-on (SSO) capability and/or improved multiple login prevention (MLP) capability.
A computer system is provided that allows participants to submit agent data structures for processing. Each agent data structure includes a valuation function for a first resource and a property of a second resource. The computer system performs a dual sided evaluation process to determine when contra-sided agents match with one another. A match is determined by comparing results of valuation functions of the agent data structures.
The described technology provides a single sign-on capability so that a user who is already signed on to a web application from a client application may not be required to sign-on again when he/she later needs access to the web application from the same or another client application. The technology also provides a multiple login prevention capability to detect multiple sign-on events using the same credentials and disable one or more of the associated multiple sessions.
A data analysis computer system is provided that receives a timeseries dataset and generates implied data from the dataset. The dataset is further vectorized to reduce the dimensionality of the data. Users provide input to identify windows of data that either positively or negatively correlate to instances of a given type of occurrence within the data. The user defined windows are converted to fixed sized windows and a machine learning algorithm constructs a model from the data. The model is used to predict instances of the given type of occurrence in newly received data. Validation of the predications may be performed.
The described technology relates to rendering a client-side user interface using a server-side cache for providing the displayed data. In an example implementation, in response to a user interface (e.g., dashboard with multiple widgets in a web application) being launched on the client device, the server initiates a refresh of the cache for the widgets; and transmits a first set of data obtained from the cache for widgets in the user interface before the cache is updated in response to the initiated refresh. The first set of data is followed by a second set of data obtained from the cache for at least some of the widgets after the cache is updated in response to the initiated refresh. The client displays the user interface using the second set of data while overwriting, for one or more of the widgets, information previously displayed using the first set of data.
H04L 67/60 - Ordonnancement ou organisation du service des demandes d'application, p. ex. demandes de transmission de données d'application en utilisant l'analyse et l'optimisation des ressources réseau requises
H04L 67/02 - Protocoles basés sur la technologie du Web, p. ex. protocole de transfert hypertexte [HTTP]
H04L 67/10 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau
The described technology relates to systems and techniques for accessing a database by dynamically choosing an index from a plurality of indexes that includes at least one learned index and at least one non-learned index. The availability of learned and non-learned indexes for accessing the same database provides for flexibility in accessing the database, and the dynamic selection between learned indexes and non-learned indexes provide for choosing the index based on the underlying data in the database and the characteristics of the query. Certain example embodiments provide a learned model that accepts a set of features associated with the query as input, and outputs a set of evaluated weights for respective features, which are then processed according to a set of rules to predict the most efficient index to be used.
A computer system is provided that communicates with a distributed blockchain computing system that includes multiple computing nodes. The exchange stores an order book and a plurality of digital wallets associated with different clients. The computer system receives new data transaction requests that are added to the order book. A match is identified between data transaction requests and hashes associated with the digital wallets associated with the respective data transaction requests are generated. The counterparties receive the hashes of the other party along with information on the match and each party causes blockchain transactions to be added to the blockchain of the blockchain computing system. The computing system then monitors the blockchain to determine if both sides of the match has been added to the blockchain.
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/06 - Circuits privés de paiement, p. ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/40 - Autorisation, p. ex. identification du payeur ou du bénéficiaire, vérification des références du client ou du magasinExamen et approbation des payeurs, p. ex. contrôle des lignes de crédit ou des listes négatives
A computer system is provided that is designed to handle multi-label classification. The computer system includes multiple processing instances that are arranged in a hierarchal manner and execute differently trained classification models. The classification task of one processing instance and the executed model therein may rely on the results of classification performed by another processing instance. Each of the models may be associated with a different threshold value that is used to binarize the probability output from the classification model.
G06F 18/241 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques
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”
The described technology relates to integrating events electronically scheduled in enterprise web applications and other event management applications. An improved capability is provided for an event management application like, for example, Microsoft's Outlook™ to provide the user with additional useful information and/or resources associated with scheduled events such as, but not limited to, meetings. Improved capabilities are provided to the enterprise web application clients based upon integration with event applications such as Outlook. Embodiments use a unique identifier generated for an event scheduled in one application for associating corresponding event information in the second application, such that the scheduled event calendars in the first and second applications can be synchronized without duplicating the event information between the two applications.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
38 - Services de télécommunications
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer software; computer software for electronic trading
of assets; computer software for trading in securities;
computer software, namely matching engine software for
processing orders on an exchange; computer software for
operating electronic markets; computer software for clearing
of trades; computer software for custody of securities;
computer software for custody of financial assets; computer
software for custody of digital assets; computer software
for risk management; computer software for detecting
financial crime; computer software for surveillance of
electronic markets; computer software for surveillance of
electronic trading; computer software for use with financial
information; computer programs for use in trading stocks and
bonds. Financial services relating to securities; stock exchange
quotation and listing services; securities exchange
services; stock trading; securities trading services;
options trading; operating an electronic market; providing
financial information; providing information relating to
securities trading; providing and updating an index based on
securities values; providing and updating an index based on
asset values; providing a financial index based on a
selected groups of securities; providing a financial index
based on a selected groups of assets; information services
relating to securities; financial information services;
computerised financial information services; providing
financial information on-line; providing financial
information by electronic means; providing financial
information via a website; providing financial information
by means of a computer database; financial information
services provided by access to a computer database;
providing information and analysis via the Internet in the
field of financial investments. Electronic data transmission; transmission of data via the
Internet; streaming of data; providing access to computer
databases; electronic network communications. Providing online, non-downloadable software; software as a
service [SaaS]; software as a service [SaaS] services
featuring software for the electronic trading of assets;
software as a service [SaaS] services featuring software for
trading in securities; software as a service [SaaS] services
featuring matching engine software for processing orders on
an exchange; software-as-a-service (SaaS) services featuring
software for operating electronic markets; software as a
service [SaaS] services featuring software for clearing of
trades; software as a service [SaaS] services featuring
software for custody of securities; software as a service
[SaaS] services featuring software for custody of financial
assets; software as a service [SaaS] services featuring
software for custody of digital assets; software as a
service [SaaS] services featuring software for risk
management; software as a service [SaaS] services featuring
software for detecting financial crime; software as a
service [SaaS] services featuring software for surveillance
of electronic markets; software as a service [SaaS] services
featuring software in the field of environmental, social,
and governance (ESG); software as a service [SaaS] services
featuring software in the field of corporate social
responsibility (CSR); software as a service [SaaS] services
featuring software for use with financial information;
software as a service [SaaS] services featuring software for
the analysis of investment portfolios; software as a service
[SaaS] services featuring software for financial asset
management; computer programming and software design;
consultancy services relating to computer programming;
design, development and programming of computer software.
94.
Systems and methods for enterprise web application dashboard management
The described technology relates to developing and/or maintaining dashboards in enterprise web applications. In some aspects, a portal web application is configured to provide a user interface on a client device to create or modify a dashboard which includes a first plurality of widgets. A second plurality of widgets includes widgets published to the portal web application from a plurality of subscriber web applications, where each of the second plurality of widgets is used in at least one of said subscriber web applications, and the first plurality of widgets includes one or more widgets from the second plurality of widgets. In some other aspects, a dashboard management service is provided by which respective enterprise web applications can create and host widgets while sharing the same with other enterprise web applications which use dashboards developed using the dashboard management service.
Systems and methods are provided for data security. A server system provides data security using one or more processor devices, one or more communication interfaces, and one or more memory devices including computer-executable instructions. Those instructions cause the one or more processor devices to: monitor one or more requests or activities of a computing device; compare the monitored one or more requests or activities with a database of predetermined characteristics to determine whether the monitored one or more requests or activities indicates that the computing device downloaded or attempted to download more than a threshold number of data files or objects; and determine that the one or more requests or activities is suspicious when the comparing determines that the one or more requests or activities indicates that the computing device downloaded or attempted to download more than the threshold number of data files or objects, which causes a response to hinder the monitored one or more requests or activities.
The described technology relates to integrating events electronically scheduled in enterprise web applications and other event applications. A capability is provided for events created by an enterprise web application and events from other external event streams to be presented in a consolidated calendar in the enterprise web application. Capabilities are also provided for sharing the calendar among enterprise users and non-enterprise users, and for efficiently generating the shared calendar.
An information computer system is provided for securely releasing time-sensitive information to recipients via a blockchain. A submitter submits a document to the system and a blockchain transaction is generated and submitted to the blockchain based on the document (e.g., the document is included as part of the blockchain transaction). An editor may edit the document and an approver may approve the document for release to the recipients. Each modification and/or approval of the document is recorded as a separate transaction on the blockchain where each of the submitter, editor, approver, and recipients interact with the blockchain with corresponding unique digital identifiers—such as private keys.
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
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
G06Q 20/02 - Architectures, schémas ou protocoles de paiement impliquant un tiers neutre, p. ex. une autorité de certification, un notaire ou un tiers de confiance
G06Q 20/06 - Circuits privés de paiement, p. ex. impliquant de la monnaie électronique utilisée uniquement entre les participants à un programme commun de paiement
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
98.
Matching techniques for data transaction requests with private attributes
A computer system is provided that includes a paired list of data transaction requests on which a matching process is performed. There are multiple different types of data transaction requests that are stored in the paired list including data transaction requests with midpoint attributes and data transaction requests with discretion attributes. The computer system may determine how the multiple different types of data transaction requests may be match against each other. Two matching processes can be used to determine if a match exists between the first and second sides of the paired list. Matches that are determined at private values are not disseminated to third-parties via public market data feeds.
A computer system is provided and programmed to assemble a plurality of synthetic datasets and blend those synthetic datasets into a synthesized dataset. An evaluation is then performed to determine whether an existing model should be associated with the synthesized dataset or a new model should be trained from an existing model using the synthesized dataset.
