Methods and apparatuses for automatic configuration and deployment of API functionality in a distributed computing environment include creating an API description defining functional features of the API and validating the API description based upon technical constraints and compliance constraints. Source code files are generated based upon the API description, and updates to the source code files are received and applied. Resources used for deployment of the API are configured in the distributed computing environment. An API build is generated based upon the updated source code. The API build is deployed and published in the distributed computing environment to enable external computing resources to access the deployed API build in the distributed computing environment.
Methods and apparatuses for optimizing performance of conversational interface applications using example forgetting include a server that retrieves training data comprising utterances each mapped to one or more known intents. The server determines a forgetting count for each utterance and selects utterances from the training data that have a forgetting count above a predetermined threshold. The server identifies whether the predicted intent associated with each utterance is accurate. The server generates updated training data comprising the selected utterances and corresponding predicted intents, and trains conversational interface applications using the updated training data. The server validates performance of the trained conversational interface applications and saves the updated training data.
A computerized method is provided for user authentication using hand gestures. Multiple points on a user's hand can be tracked using cameras or various sensors and the motion of those points in space and relative to each other can used to create gesture-based passwords. Such user authentication techniques have advantages in augmented and virtual reality applications where traditional text-based passwords may be difficult. Gesture-based user authentication can be augmented with physical characteristics of the specific user's fingers and hands including size, shape, and distinguishing marks to enhance security.
Techniques are provided for managing and transforming alerts generated for cloud computing environments. An alert corresponding to a predefined service name is identified. The alert is transformed with enriched data and into a particular format/syntax such that all generated transformed alerts are consistent in terms of format/syntax. The transformed alert is compared to other existing alerts to determine if the transformed alert is new or repetitive. If the transformed alert is new and does not correspond to a paused event, the transformed alert is published. If the transformed alert is repetitive or corresponds to a paused event, the transformed alert is prevented from being published. The enriched data of the transformed alert can include cloud application specific information and other cloud environment specific information not included in the original alert. The enriched data can be used to more effectively monitor/remediate cloud environment issues.
H04L 41/0604 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant du filtrage, p. ex. la réduction de l’information en utilisant la priorité, les types d’éléments, la position ou le temps
H04L 41/0631 - Gestion des fautes, des événements, des alarmes ou des notifications en utilisant l’analyse des causes profondesGestion des fautes, des événements, des alarmes ou des notifications en utilisant l’analyse de la corrélation entre les notifications, les alarmes ou les événements en fonction de critères de décision, p. ex. la hiérarchie ou l’analyse temporelle ou arborescente
7.
SYSTEMS AND METHODS FOR MEASURING PERFORMANCE OF LARGE LANGUAGE MODELS
Therefore, what is needed are systems and methods for measuring the performance of a large language models (LLM). As described herein, the system generates measurement tools that are capable of accurately determining whether a predicted answer generated by an LLM is correct (in view of the corresponding question and/or reference answer). In addition, because the system does not suffer from the effects of AI hallucinations (and therefore can provide the correct determination), such determination can be performed without the need for a human to check whether the LLM is correct.
Methods and apparatuses for evaluating probabilistic fairness of machine learning (ML) classification models include a server that generates a first input data set, including assigning a class membership label to each of a plurality of participants based upon a probability of class membership derived from a surrogate class variable. The server generates a second input data set, including assigning a class membership label to each of the plurality of participants based upon ground truth class values. The server executes a binary classification model on the first input data set to generate inferred fairness metrics for the binary classification model. The server executes the binary classification model on the second input data set to generate actual fairness metrics for the binary classification model. The server determines a disparity in one or more fairness metrics for the binary classification model based upon a comparison of the inferred fairness metrics to the actual fairness metrics.
A computerized method is provided for holistic evaluation of a containerized microservice's health. Methods can include passively monitoring and recording interactions with the resources the microservice depends on to assess the health of those resources and comparing to selected thresholds to determine potential recovery actions.
Methods and apparatuses for guided content recommendation using a knowledge graph include a server which determines a user intent associated with a user interaction request. The server determines a graph state associated with a user of a remote device based upon historical traversal information. The server identifies a seed node of a content recommendation knowledge graph based upon the user intent and the graph state. The server generates a digital content display for presentation at the remote device recommended digital content items from the seed node. The server computing device traverses the knowledge graph from the seed node to a connected node based upon a response to the digital content display, including updating the graph state associated with the user of the remote device.
45 - Services juridiques; services de sécurité; services personnels pour individus
36 - Services financiers, assurances et affaires immobilières
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Providing a website featuring information in the fields of personal relationships and personal relationship communication practices and services. Providing information online in the field of wealth management relating to intrafamily relationships and intergenerational wealth; providing information in the field of wealth management; financial advisory services, namely, wealth preservation and intergenerational wealth transfer planning services. Production and distribution of videos in the field of family management and relationships; publication of on-line non-downloadable articles in the field of in the field of family management and relationships; publication of on-line newsletters in the field of family management and relationships; online publication of blogs in the field of family management and relationships; education services, namely, production and distribution of non-downloadable webinars in the field of family management and relationships; entertainment services, namely, production and distribution of podcasts in the field of family management and relationships.
45 - Services juridiques; services de sécurité; services personnels pour individus
36 - Services financiers, assurances et affaires immobilières
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Providing a website featuring information in the fields of personal relationships and personal relationship communication practices and services Providing information online in the field of wealth management relating to intrafamily relationships and intergenerational wealth; providing information in the field of wealth management; financial advisory services, namely, wealth preservation and intergenerational wealth transfer planning services Production and distribution of videos in the field of family management and relationships; publication of on-line non-downloadable articles in the field of in the field of family management and relationships; publication of on-line newsletters in the field of family management and relationships; online publication of blogs in the field of family management and relationships; education services, namely, production and distribution of non-downloadable webinars in the field of family management and relationships; entertainment services, namely, production and distribution of podcasts in the field of family management and relationships.
14.
SYSTEM AND FRAMEWORK FOR MULTICHANNEL VOICE OF CUSTOMER
A method for integrating customer interaction data from a plurality of channels and for a plurality of customers includes receiving a plurality of customer interaction records, each record associated with a channel and an identifier of a customer, each record including a customer interaction transcript; providing the plurality of customer interaction transcripts to a machine learning model; causing execution of the machine learning model, resulting in a model output including an interaction theme and an interaction summary associated with each one of the customer interaction transcripts; clustering the plurality of themes using a multi-level taxonomy, resulting in a plurality of clustered themes associated with each one of themes; mapping the pluralities of clustered themes and the plurality of interaction summaries, resulting in an interaction reason associated with each one of the customer interaction records; storing the interaction reason associated with each one of the customer interaction records in a database.
A method for generating cross-channel recommendations for a customer includes receiving customer data associated with the customer, content data, and clickstream data; encoding the content data using a text encoder, the encoding resulting in content embeddings; encoding the clickstream data using a clickstream encoder, the encoding resulting in clickstream embeddings; providing the content data, the clickstream data, and the clickstream embeddings as inputs to a hybrid latent model; causing execution of the hybrid latent model, the execution resulting in cross-system user and item interaction embeddings; retrieving application features corresponding to the clickstream data from an application feature store; providing the customer data, the content embeddings, the clickstream embeddings, the cross-system user and item interaction embeddings, and the application features as inputs to a recommendation model; causing execution of the recommendation model, the execution resulting in a plurality of ranked recommendations.
Techniques are provided for proactive analysis of a computer environment to prevent a disruption in services. Specifically, a risk score may be generated for each of a plurality of different alerts. If the risk score generated for a particular alert meets a predefined criterion, the alert may be amplified to determine a remediation for the computer environment. Specifically, an alert with a risk score that meets a predefined criterion may be amplified to determine one or more remediations that can be implemented to proactively prevent a future and potential disruption in services in a computer environment. For example, a service process that has a greatest utilization at a particular storage resource, e.g., storage array, may be identified. One or more query scripts may then be executed within the database using the particular storage resource to identify a remediation that can be implemented to prevent a potential future disruption in services.
Methods and systems for automated testing of virtual reality software applications using robotic devices include a server that converts a test workflow description into a sequence of actions in a format interpretable by a robotic device. The server transmits the sequence of actions to the robotic device. For each action in the sequence of actions, the server a) receives, from the robotic device, execution data corresponding to an outcome of execution of the action by the robotic device; b) captures, from a virtual reality device, one or more of image data and vector data corresponding to a current state of a virtual reality software application; c) analyzes one or more of the image data, the vector data, and the execution data to determine whether the robotic device successfully executed the action; and d) upon determining that the robotic device successfully executed the action, repeats steps a)-d) for the next action.
A computerized method is provided for automatic monitoring, deserializing, cataloging, and replaying messages passing through a trading platform. Methods can include an audit micro service operable to read JSON files associated with various messages including a topic and class name attribute and create a message consumer having specific attributes based on the topic and class name attribute. The consumer can be a compiled executable operable to receive, deserialize, and store messages in a searchable database in human readable format.
Methods and apparatuses for constraint-based optimization of machine learning classification models include determining performance constraints associated with deployment and execution of a model and identifying candidate pipelines. For each candidate pipeline, a model is trained using a training dataset, the trained model is executed using a testing dataset to determine performance characteristics for the trained model, and the performance characteristics are compared to the performance constraints. One of the candidate model pipelines that meets the performance constraints is identified and a production model is built based upon the identified candidate pipeline. The production model is deployed to a production computing environment for execution.
Systems, methods, and media for automatically and dynamically generating and executing chaos testing for different software applications executing in a computing environment
Techniques are provided for automatically generating and executing chaos tests for different software applications in a computing environment. A chaos testing data structure can be generated based on an analysis of configuration and/or property files for the software application and/or hosting platform service provider. A pattern and other information from the chaos data structure can be used to determine a topology of the software application and determine defined paths to different identified potential points of failure. One or more components can be selected for the defined paths to the identified potential points of failure. A chaos test template can be selected and automatically populated for each selected component. One or more chaos tests can be executed using the populated chaos test templates to identify one or more vulnerabilities/weaknesses, determine one or more recommendations to improve the vulnerabilities/weaknesses, and/or automatically implement one or more remediations to improve the vulnerabilities/weaknesses.
Methods and apparatuses for provisioning a database management platform in a cloud computing environment include a server that reserves virtual computing resources in the cloud environment. The server provisions a database management platform using the reserved virtual computing resources. The database management platform includes primary and secondary database instances, a database observer instance, and a platform monitor agent. The server configures a database observer instance to monitor availability of database instances and to route traffic to other database instances. The server integrates the database management platform with an identity authentication service, monitors operational status of the database management platform using a monitoring service, and refreshes the reserved virtual computing resources in the database management platform using a rehydration service.
Methods and apparatuses for conversation dialogue orchestration in virtual assistant communication sessions include a server that establishes a chat session between a virtual assistant (VA) application and a client device. The VA application captures an utterance generated by a user and processes the utterance to instantiate a dialogue behavior tree comprising workflow agents each associated with executable code for completing a corresponding workflow action. The VA application traverses the behavior tree to generate a response to the utterance, including evaluating one or more conditions associated with a workflow agent to determine whether to execute the code in the workflow agent, and when the conditions associated with the workflow agent are met, executing the code to complete the workflow action and storing a sub-response in a dialogue memory. The VA application coalesces the sub-responses to generate a final response and transmits the final response to the client device.
G06F 40/35 - Représentation du discours ou du dialogue
H04L 51/02 - 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 en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
A computerized method is provided for automated deletion of data. Methods can include identification of personally identifiable information (PII) or other data that may be subject to regulation. Methods can include creating an encrypted record of deletion for future verification. In some embodiments, the record may include PII and the record may be encrypted via a one-way cryptographic hash such that foreknowledge of the PII is required to search the deletion record.
G06F 21/00 - Dispositions de sécurité pour protéger les calculateurs, leurs composants, les programmes ou les données contre une activité non autorisée
Methods and systems for efficient caching and retrieval of responses in conversation service applications includes a server that captures an utterance and converts the utterance into an utterance index key. The server searches a first response cache to determine whether the utterance index key matches a response index key. When there is a match, the server transmits a response that matches the utterance index key to a client device. When there is not a match, the server converts the utterance into an utterance embedding and searches a second response cache to identify a response embedding. The server captures a fuzzy response index key associated with the closest matching response embedding and searches the first response cache to identify a response index key that matches the fuzzy response index key.
G06F 40/40 - Traitement ou traduction du langage naturel
G06F 16/31 - IndexationStructures de données à cet effetStructures de stockage
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
G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence
25.
Automating software application infrastructure deployment in a cloud computing environment
Methods and apparatuses for automating software application infrastructure deployment in a cloud computing environment include defining hierarchical infrastructure layers for a software application, generating a deployment pipeline for the software application comprising pre-coded resource configuration modules, and triggering execution of the deployment pipeline to deploy the software application in the cloud computing environment.
Methods and apparatuses are described for user authentication during an electronic signature workflow. A server authenticates user credentials included in an electronic signature request. The server generates activity variables based upon parameters associated with the electronic signature request. The server creates a multidimensional vector using the activity variables. The server executes a trained machine learning classification model on the multidimensional vector to generate an anomaly score for the electronic signature request. The server determines additional authentication requirements for the electronic signature request based upon the anomaly score. The server initiates the additional authentication requirements for the electronic signature request, including validating user authentication data received from remote computing devices.
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
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
A computerized method is provided for automatic monitoring and detection of deposit fraud. Methods can include receiving, by a computing device, user account information, assessing the user account information to determine a fraud risk score and, if sufficient, adding the account to a watchlist for additional monitoring.
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
G06Q 20/10 - Architectures de paiement spécialement adaptées aux systèmes de transfert électronique de fondsArchitectures de paiement spécialement adaptées aux systèmes de banque à domicile
28.
SYSTEMS, METHODS, AND MEDIA FOR GENERATING AND UTILIZING AN INTERACTIVE DIRECTED GRAPH REPRESENTING AN MQ ENVIRONMENT
Techniques are provided for generating and utilizing an interactive directed graph representing a messaging queue (MQ) environment. A plurality of text files, each corresponding to a different queue manager of the MQ environment may be analyzed. Based on the analysis, (1) each queue manager and the objects managed by the queue manager may be identified and (2) the relationships between the objects of the MQ environment may be identified. An interactive directed graph, representing the MQ environment, can be generated to include a different node for each identified object and an edge for each identified relationship. The interactive directed graph can provide a pictorial representation for the flow of data through the entire MQ environment. The interactive directed graph can be analyzed and searched to (1) identify a portion that includes one or more objects of interest and/or (2) identify a problem in the MQ environment and remediate the problem.
The End-to-End Encryption and Hot Wallet Key Recovery Apparatuses, Processes and Systems (“E2EEHWKR”) transforms key backup request, key recovery request datastructure/inputs via E2EEHWKR components into key backup response, key recovery response outputs. A key backup request datastructure specifying a wallet private key, a private key backup server identifier, a PIN shard fracture scheme definition, and a plurality of PIN shard backup devices is obtained. A user security PIN is obtained and utilized to encrypt the wallet private key. A symmetric key is calculated from a public key associated with the private key backup server identifier and an app private key. The encrypted wallet private key is encrypted utilizing the symmetric key. The twice encrypted wallet private key is sent to a private key backup server. The user security PIN is encrypted utilizing an asymmetric keypair. Encrypted user security PIN shards are generated and sent to PIN shard backup devices.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
A method for identifying the presence of a logo in an image includes providing a neural network having an image encoder, a text encoder, and a score calculator. The method includes receiving the image and a textual description associated with the logo. The method further includes providing the image to the image encoder and the textual description to the text encode. The method includes executing the image encoder and the text encoder, wherein the image encoder generates one or more image embeddings from the image and the text encoder generates one or more text embeddings from the textual description. The method further includes executing the score calculator, wherein the score calculator generates a score from the one or more image embeddings and the one or more text embeddings. The method also includes determining the presence of the logo in the image based on the score.
G06F 40/284 - Analyse lexicale, p. ex. segmentation en unités ou cooccurrence
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 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 10/86 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les représentations syntaxiques ou structurelles du motif d’image ou vidéo, p. ex. reconnaissance des chaînes symboliquesDispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant des correspondances graphiques
31.
DIALOG CONTROL FLOW FOR INFORMATION RETRIEVAL APPLICATIONS
Methods and apparatuses are described for dialog control flow in information retrieval applications. A server establishes a chat-based communication session between an information retrieval application and a client device. The server determines a user intent from utterances received from a user of the client device and initiates a first dialog workflow associated with the user intent. The server invokes NLP services using the utterances to determine a comprehension score for the user intent and identifies a first one of the NLP services to continue the first dialog workflow when the comprehension score is at or above a threshold value, including generating a response to the utterances using the first NLP service. The server delegates the communication session to a second dialog workflow when the comprehension score is below the threshold value, including invoking a generalized language processing service associated with the second dialog workflow using the user intent to generate a response to the utterances. The server transmits the generated response to the client device as part of the chat-based communication session.
H04L 51/02 - 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 en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
G06F 40/35 - Représentation du discours ou du dialogue
G10L 15/183 - Classement ou recherche de la parole utilisant une modélisation du langage naturel selon les contextes, p. ex. modèles de langage
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
32.
Decentralized Exchange with Price Oracle Apparatuses, Processes and Systems
The Decentralized Exchange with Price Oracle Apparatuses, Processes and Systems (“DEPO”) transforms decentralized exchange liquidity provision request, decentralized exchange crypto asset swap request, decentralized exchange liquidity redemption request datastructure/inputs via DEPO components into decentralized exchange liquidity provision response, decentralized exchange crypto asset swap response, decentralized exchange liquidity redemption response outputs. A decentralized exchange liquidity provision transaction is obtained via a bidirectional decentralized exchange smart contract deployed on a blockchain. A crypto assets exchange quotient for exchanging a first crypto asset type and a second crypto asset type is determined. A quantity of fungible tokens specific to a crypto assets liquidity tranche datastructure to generate is calculated. The calculated quantity of fungible tokens specific to the crypto assets liquidity tranche datastructure is transferred to a provision blockchain address controlled by a sender of the decentralized exchange liquidity provision transaction.
G06Q 40/04 - TransactionsOpérations boursières, p. ex. actions, marchandises, produits dérivés ou change de devises
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 30/0201 - Modélisation du marchéAnalyse du marchéCollecte de données du marché
A computer-implemented system is provided for configuring and managing a federation ecosystem implemented in a data query language and comprising a plurality of subgraphs. The system includes a sandbox registry in communication with the subgraphs. The sandbox registry is configured to test and verify changes to the subgraphs to ensure validity of the subgraphs. The system also includes a global registry in communication with the sandbox registry. The global registry is configured to register the subgraphs after the subgraphs are tested and verified by the sandbox registry. The system further includes a portal in communication with the global registry. The portal is configured to present to a user the subgraphs registered with the global registry and receive from the user instructions for combining two or more of the subgraphs to form at least one supergraph.
The Decentralized Exchange with Price Oracle Apparatuses, Processes and Systems (“DEPO”) transforms decentralized exchange liquidity provision request, decentralized exchange crypto asset swap request, decentralized exchange liquidity redemption request datastructure/inputs via DEPO components into decentralized exchange liquidity provision response, decentralized exchange crypto asset swap response, decentralized exchange liquidity redemption response outputs. A decentralized exchange liquidity provision transaction is obtained via a unidirectional decentralized exchange smart contract deployed on a blockchain. A crypto assets exchange quotient for exchanging a source crypto asset type and a target crypto asset type is determined. An imbalance rule check for a crypto assets liquidity tranche datastructure is executed. A non-fungible token specific to the crypto assets liquidity tranche datastructure is minted. The non-fungible token is associated with a provision blockchain address controlled by a sender of the decentralized exchange liquidity provision transaction.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
A computer-implemented method is provided for producing a test for a software application that is generated based on metadata. The method includes providing to the user a library of predefined test logic for testing multiple software components. Each software component is a reusable element comprising application logic, visual styling and user interface. The method also includes guiding the user to define (i) at least one execution path that specifies an order for testing one or more pages of the software application, and (ii) test instructions for one or more components on each of the one or more pages. The method further includes retrieving, from the library, predefined test logic for the one or more components if they are present in the library based on the test instructions supplied by the user, and automatically configuring a test file incorporating the predefined test logic in an order specified by the execution path.
A computer-implemented method for adaptively discretizing a position of a textual object in a document includes receiving, by a computer system, an image of the document and determining, by the computer system, an absolute position of the textual object in the image of the document. The method further includes normalizing, by the computer system, the absolute position to determine a relative position of the textual object. The method also includes calculating, by the computer system, a bin size such that at least one axis of the image is divided into a plurality of separate bins, wherein a distance between each bin along the at least one axis and its adjacent bin equals the bin size. The method includes discretizing, by the computer system, the relative position based on the bin size to determine a discretized position of the textual object; and providing, by the computer system, the discretized position and a textual content of the textual object as an input to a machine learning model.
G06V 30/19 - Reconnaissance utilisant des moyens électroniques
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 30/413 - Classification de contenu, p. ex. de textes, de photographies ou de tableaux
G06V 30/414 - Extraction de la structure géométrique, p. ex. arborescenceDécoupage en blocs, p. ex. boîtes englobantes pour les éléments graphiques ou textuels
Systems and methods are described for enhancing performance of a search engine by using pre-existing fine-tuned machine learning models that include domain-specific knowledge. A computing device receives search results from a search engine based on a query, in which the search results include chunk identifiers and a first weight score associated with each chunk identifier. The computing device further determines a subset of search results, which includes a first predetermined number of top-ranked chunk identifiers in the search results. The computing device generates, for each chunk identifier in the subset of search results, one or more second weight scores. Then the computing device generates, via a machine learning model, ensemble scores for the chunk identifiers. Afterwards, the computing device determines a second predetermined number of top-ranked chunk identifiers based on the ensemble scores.
Automatic transaction processing failover and reconciliation in a cloud-based environment includes monitoring the processing of transaction messages to identify exception events and determining whether to initiate a failover switch based upon the identified exception events. When a failover switch is initiated, the system identifies a target cloud-based system instance for the failover switch, changes a state of the affected cloud-based system instance to prevent the affected instance from receiving transaction messages, changes a state of the target instance to receive transaction messages intended for the affected instance, and performs a replication check between databases. The system reconciles transaction messages stored in the database of the cloud-based system instance to identify anomalies.
G06F 11/20 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel en utilisant un masquage actif du défaut, p. ex. en déconnectant les éléments défaillants ou en insérant des éléments de rechange
A method for determining regression of a database query associated with a first execution plan includes receiving a first performance measure for the database query and the first execution plan; determining a presence of at least one stored performance measure for the database query in a data repository; adding the first performance measure and identifiers for the database query and the first execution plan to a synchronization list; retrieving a second performance measure associated with a second execution plan from the data repository; determining a regression of the database query by comparing the first performance measure to the second performance measure; in response to a determination that the database query is regressed, adding the first performance measure, the second performance measure, and identifiers for the database query and the first execution plan to a regression report.
The Serverless Computing for Portfolio Optimization Apparatuses, Processes and Systems (“SCPO”) transforms optimization application configuration input, optimization application execution input datastructure/inputs via SCPO components into optimization application configuration output, optimization application execution output outputs. An optimization application configuration request associated with an optimization application and structured to specify a plurality of optimization modules to configure for the optimization application is obtained. A first optimization configuration datastructure structured to specify a first cloud function, a first API path, and an identifier of an application load balancer is generated for a first optimization module. A second optimization configuration datastructure structured to specify a second cloud function, a second API path, and the identifier of the application load balancer is generated for a second optimization module. The first optimization configuration datastructure and the second optimization configuration datastructure are provided to a cloud configuration server structured to configure the application load balancer.
Methods and apparatuses for automatic ingestion of data using a rate-limited application programming interface (API) include a computing device that creates structured query objects, each comprising instructions for retrieving data from a repository using the rate-limited API. The computing device requests data from the repository via the rate-limited API using the structured query objects and a plurality of API access tokens, including a) generating data requests, each comprising a structured query object; b) determining a transmission delay for each API access token based upon a current rate limit imposed by the rate-limited API; c) transmitting each data request to the repository via the rate-limited API using an API access token that has a transmission delay below a threshold value; and d) processing data received from the repository in response to each data request. The computing device repeats steps b) through d) until data responsive to each data request is received.
A method for calculating counterparty risk using a risk calculation application includes receiving a plurality of transactions in a portfolio, each including a market value and a beta value. The method includes generating, in parallel, a plurality of market scenarios based on a log-normal distribution. The method also includes calculating, in parallel, an average market scenario and a high-risk market scenario based on the plurality of market scenarios. The method further includes calculating, in parallel, a beta-adjusted portfolio value based on the plurality of market values and the plurality of beta values. The method includes calculating, an expected portfolio exposure based on the beta-adjusted portfolio value and the average market scenario. The method also includes calculating a potential portfolio exposure based on the beta-adjusted portfolio value and the high-risk market scenario. The method includes storing the expected portfolio exposure and the potential portfolio exposure in a database.
Methods and apparatuses for multimodal enhancement of interactions in conversation service applications include a server that establishes a chat-based communication session between a conversation service application and a client computing device. Query input is captured from a user during the session. The server converts an audio segment corresponding to a video into a video transcript using speech recognition, and determines a transcript portion for the video that is responsive to the query input using a dense passage retriever model. The server selects video frames from the video that correspond to the transcript portion and determines, for the selected frames, a predicted relevancy between the selected frame and the query input. The server generates a response to the query input comprising the selected frames based upon the relevancy. The server transmits the response to the client device for display.
G06F 16/78 - Recherche de données caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/783 - 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
51.
Real-Time System Progression Optimizer Apparatuses, Processes and Systems
The Real-Time System Progression Optimizer Apparatuses, Processes and Systems (“RTSPO”) transforms system progression simulation input, system progression simulation update input datastructure/inputs via RTSPO components into system progression simulation output, system progression simulation update output outputs. A system progression simulation request datastructure structured as specifying a set of initial scenario parameters values for a set of scenario parameters is obtained. A set of parameter evaluation values for each scenario parameter in the set of scenario parameters is determined. A set of scenario evaluation points is determined. A scenario result value for each scenario evaluation point is computed via a system progression simulation. A set of surface descriptor datastructures is determined. A scenario evaluation datastructure structured as specifying an evaluation function determined via interpolation is generated for each surface descriptor datastructure. A scenario result value for the set of initial scenario parameters values is determined via a matching scenario evaluation datastructure.
Computerized methods and apparatuses, including computer program products, for guided workflow processing include a server computing device which determines a guided workflow transaction path based upon input received from a first client device. The server initiates a transaction based upon the transaction path, including capturing data elements associated with a user of a second client device. The server stores the captured data elements, including a transaction identification token and a state of the transaction path. The server receives a request to continue the transaction from the second client device and retrieves the data elements. The server generates a user interface form based upon the state of the transaction path and displays the user interface form on the second client device. The server processes the transaction based upon input received from the second client device via the user interface form.
Methods and apparatuses are described for providing a centralized treatment selector for providing personalized cross-channel treatments for a given user. A computing device of a system establishes a first communication session with a user in a first channel. The system receives, at a treatment selector application, a user identifier and an experience context from the first channel. The system retrieves, from a treatment map store, one or more treatment maps compatible with the experience context, wherein the one or more treatment maps comprise an eligibility rule. The system obtains customer attributes for the user from an attribute store using the user identifier. One or more treatment maps and the customer attributes are provided to an eligibility rule engine that in turn identifies a set of eligible treatment maps based on the customer attributes and the eligibility rules for each of the one or more treatment maps. Identifiers for one or more of the set of eligible treatment maps are returned to the first channel. The first channel retrieves and applies, using the identifiers, a treatment map selected from the set of eligible treatment maps using a treatment catalog.
A method for processing a software application workflow using a workflow engine includes receiving a workflow configuration defining the workflow including a plurality of nodes and a plurality of connections between the nodes, each of the nodes associated with a corresponding software processing task. The method includes determining a first set of nodes of the plurality of nodes to be executed based on the workflow configuration and the plurality of connections. The method includes causing execution of the software processing tasks associated with the first set of nodes, resulting in an execution result. The method includes determining a second set of nodes of the plurality of nodes to be executed based on the workflow configuration, the plurality of connections, and the execution result. The method includes causing execution in parallel of the tasks associated with the second set of nodes.
The Distributed Benefits Coverage Validation Apparatuses, Processes and Systems (“DBCV”) transforms provider info, add provider transaction request, employee subscriber ID card data datastructure/inputs via DBCV components into add provider transaction response, benefit coverage validation notification outputs. A benefit coverage validation request datastructure structured to specify subscriber ID card data associated with a beneficiary is obtained. A blockchain address of a smart contract associated with the beneficiary is determined via the subscriber ID card data. Encrypted benefit coverage data associated with the beneficiary is obtained by sending a blockchain transaction to the blockchain address of the smart contract. An encryption key corresponding to the encrypted benefit coverage data is obtained from a key management server. The encrypted benefit coverage data associated with the beneficiary is decrypted with the encryption key. The decrypted benefit coverage data is evaluated to determine a benefit status corresponding to a benefit provided by a provider.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Downloadable computer software using artificial intelligence for review and approval of public communications; downloadable computer software that uses artificial intelligence models to quickly scan, score and analyze sales brochures, fact sheets, infographics, whitepapers, financial reports, flyers and social media content, and generates a risk analysis report based on analyzed data; downloadable computer software, accessible via application programming interfaces (apis), for review and approval of communications and documents (1) Providing temporary use of non-downloadable computer software using artificial intelligence for review and approval of public communications; providing temporary use of online non-downloadable computer software that uses artificial intelligence models to quickly scan, score and analyze sales brochures, fact sheets, infographics, whitepapers, financial reports, flyers and social media content, and generates a risk analysis report based on analyzed data; providing temporary use of non-downloadable computer software, accessible via application programming interfaces (apis), for review and approval of communications and documents; software as a service (saas) featuring software for use in business and financial risk management, namely regulatory compliance, financial crimes compliance, business intelligence, market and collateral risk management, identity management, personnel screening and background investigations, fraud prevention and detection, regulatory compliance analytics, customer due diligence, third- and fourth-party risk management, corporate protective intelligence, hospitality, and travel safety
57.
Automated software container rehydration and deployment
Methods and apparatuses for automated software container rehydration and deployment include a server that updates a container image for a software application by modifying layers of the container image and deploying the updated container image as a first container in a passive production environment. For a plurality of traffic volumes, the server: a) increases application traffic directed to the first container to a first traffic volume, b) monitors service level indicators associated with performance of the first container, c) increases the application traffic directed to the first container to a higher traffic volume upon determining that the service level indicators are within a performance threshold, and d) repeats steps b) and c) until the application traffic is increased to a highest traffic volume and the service level indicators are within the performance threshold. The server deploys the updated container image as a second container in an active production environment.
Methods and apparatuses are described for automatic intelligent query suggestion for information retrieval applications. A server a) determines candidate intents associated with user input text received from a remote device, including applying a trained intent classification model to the user input text to predict candidate intents. The server b) calculates a likelihood value for each of the candidate intents. The server c) compiles a list of suggested queries based upon the candidate intents and associated likelihood values. The server d) identifies a subset of the list of suggested queries for display on the remote device. Upon detecting an update to the user input text at the remote device, the server repeats steps a) to d) using the updated user input text, or upon detecting a selection of one of the suggested queries at the remote device, the server retrieves content responsive to the selected query.
Techniques are provided for generating and using a multi-signature token for electronic message validation according to the one or more embodiments as described herein. Specifically, a multi-signature token may be generated that includes at least two digital signatures and information (e.g., user information). Each of the at least two digital signatures may be generated using a private key of at least two key pairs that are maintained on a plurality of keystores that have at least two different implementations (e.g., security protocols). If the at least two digital signatures are valid, the multi-signature token may be determined to be valid and the client request may optionally be performed. If at least one of the at least two digital signatures is invalid, the client request is optionally not performed.
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 method for evaluating electronic documents based on a framework having a plurality of labels includes receiving a plurality of electronic documents, each electronic document having a company identifier. The method includes extracting a plurality of input sentences from each electronic document. The method includes generating a plurality of input sentence embeddings, each input sentence embedding corresponding to one of the input sentences. The method includes generating a plurality of label embeddings, each label embedding corresponding to one of the labels. The method includes calculating a plurality of similarity measures between each of the input sentence embeddings and each of the label embeddings. The method includes generating a plurality of label sentences for each of the labels based on the similarity measures, each of the label sentences being associated with one of the company identifiers. The method includes generating a plurality of entities for each of the label sentences.
G06V 30/19 - Reconnaissance utilisant des moyens électroniques
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
A computer implemented method is provided for assisting an agent in providing feedback to a customer during a chat session. The method includes receiving live feedback from the agent to the customer in response to an inquiry from the customer. The method also includes determining if at least one automated response is needed by comparing and matching the live feedback with at least one predefined trigger pattern. The method further includes identifying one or more trigger phrases in the live feedback if automated response is needed and determining from a conversation history database at least one automated response based on the one or more trigger phrases. The method additionally includes appending the at least one automated response to the live feedback for presentation to the customer during the chat session.
A method for reconciling data includes separating a first table into a plurality of first chunks, each first chunk including a plurality of first rows, and second table into a plurality of second chunks, each second chunk including a plurality of second rows. Each second chunk corresponds a first chunk. For each first chunk, the method includes: computing a first hash based on the first chunk and a second hash based on a second chunk corresponding to the first chunk; comparing the first hash with the second hash; in response to the first hash being different from the second hash, retrieving the plurality of first rows and the plurality of second rows and comparing the plurality of first rows to the plurality of second rows; in response to the first rows being different from the second rows, generating executable code configured to reconcile the first table with the second table.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
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 method for customer service representative training via a conversation with a simulated customer includes: receiving a profile of a simulated customer; causing display of the profile of the simulated customer; generating a plurality of textual prompts associated with the simulated customer and based on the profile of the simulated customer; generating a plurality of audio prompts associated with the simulated customer, each one corresponding to one of the textual prompts; playing each one of the plurality of audio prompts. The method also includes receiving a plurality of audio responses associated with the customer service representative, each one in response to a corresponding one of the audio prompts; generating a plurality of textual responses associated with the customer service representative, each one corresponding to one of the audio responses; storing the plurality of textual prompts and the plurality of textual responses in a database.
Methods and apparatuses are described for generating parallel synthetic training data for a machine learning model. A server computing device generates a model training dataset from a baseline dataset comprising a plurality of sentences labeled as noncompliant with a ruleset. The server trains a conditional autoregressive language model using the model training dataset as input to generate a corpus of synthetic predicted to be noncompliant with the rulesets. For each synthetic sentence, the server executes a compliance classification model to generate a compliance label for the synthetic sentence. The server identifies a plurality of the synthetic sentences labeled as noncompliant that are semantically similar to sentences from the baseline dataset to generate a first parallel corpus of synthetic training data. The server executes a language suggestion model using the identified synthetic sentences to generate a second parallel corpus of synthetic training data.
A computer-implemented method is provided for automatically classifying a selected transaction. The method includes receiving historical data comprising a plurality of historical transactions assigned to respective ones of a plurality of transaction classes and preprocessing historical data, including (i) correlating portions of the historical data to respective ones of the plurality of transaction classes and (ii) cleansing the historical data. The method also includes tokenizing the preprocessed historical data portion and vectorizing the plurality of tokens generated. The method further includes generating a classifier for predicting transaction classes for incoming transaction data and providing data related to the selected transaction to the classifier to generate a prediction of a transaction class for assignment to the selected transaction.
Methods and systems are described for web object maintenance in a software application testing environment using reinforcement learning. A server detects failure of a test script caused by a web object of the software application. The server identifies the web object that caused the failure using code elements extracted from a webpage, including: determining, for each code element, actions to be performed against the code element, executing a deep neural network model to generate a reward value by applying each action to properties of the code element, selecting the code element having a maximum reward value, and classifying the code element upon comparing properties of the selected code element to properties of web objects in a repository. The server updates a web object in the repository to comprise the selected code element and the properties. The server resumes execution of the test script using the updated web object.
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
A method for analyzing and improving a configuration of an executable event-based application includes receiving, by a computer system, the configuration of the event-based application and the event-based application. The method includes linting the configuration. The method further includes generating a predicted performance of the application in relation to the event streaming platform using a machine learning model. The method also includes generating, at least one first recommendation, based on the predicted performance, for improving the configuration. The method includes applying the at least one first recommendation to the configuration. The method includes executing the application. The method further includes measuring an actual performance of the application in relation to the event streaming platform. The method also includes generating at least one second recommendation based on the actual performance of the application that fine-tunes a corresponding one of the at least one first recommendation.
Methods and systems for secure geolocation-based data access control include a server that captures a data access request from a remote device and determines whether the requestor geolocation corresponds to a non-restricted zone or a restricted zone. The server determines whether the requestor identity has permission to receive a full view or a masked view of data. The server retrieves data responsive to the data query and generates a response to the data access request, the response including a full view or a masked view of the retrieved data. When the generated response comprises a masked view, the server determines that the user of the remote device has requested a full view of the responsive data, authenticates the remote device using the requestor identity, and updates the generated response to comprise the full view of the retrieved data. The server device transmits the generated response to the remote device.
A computer implemented method is provided for creating and using a secret zero by multiple participants in a group. The secret zero is representative of a master secret that protects other secrets. The method includes creating, by a computing device of each participant, a message comprising a second public key, a commitment to a polynomial, a plurality of encrypted private key shares assigned to the other participants, a plurality of signatures associated with the private key shares assigned to the other participants, and a commitment of a symmetric key. The method also includes broadcasting, by the computing device of each participant, an encrypted version of the message to the group of participants. The method further includes broadcasting, by the computing device of each participant, the symmetric key to the group after all other participants have completed broadcasting their messages.
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
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Software as a service (saas) featuring web-based computer software platforms for investors to manage financial data, crypto-asset data, financial data analytics, financial alternative data, and financial research data.
71.
Automated intelligent correction of erroneous data in a transaction dataset
Automated intelligent correction of erroneous data for uninterrupted transaction processing includes a server that captures real-time transaction data from a transaction message stream. The server determines errors in the real-time transaction data for the transaction. The server identifies a trained artificial intelligence (AI) model from a plurality of trained AI models based upon the determined errors and executes the identified AI model using the real-time transaction data as input to correct the errors. The server determines a workflow state of the transaction using the real-time transaction data. The server generates a message for insertion in the transaction message stream, the message comprising the corrected real-time transaction data. The server inserts the generated message in the transaction message stream.
The NFT Based Secure Authentication and Notification Apparatuses, Processes and Systems (“NBSA”) transforms authenticating NFT generation input, NFT authentication input, document publishing input, NFT document access input datastructure/inputs via NBSA components into authenticating NFT generation output, NFT authentication output, document publishing output, NFT document access output outputs. An NFT authentication request datastructure is obtained. An owner blockchain address is determined. Authorization data is evaluated to verify that the authorization data establishes control over the owner blockchain address. An NFT metadata datastructure is obtained. A master hash associated with the authenticating NFT identifier is determined. A set of source asset datastructures associated with the authenticating NFT identifier is determined. For each respective source asset datastructure, a hash of source asset data is determined. A master hash is generated from the determined hashes. Match between the retrieved master hash and the generated master hash is verified. An authentication success indication is provided.
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
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
73.
NFT based secure authentication and notification apparatuses, processes and systems
The NFT Based Secure Authentication and Notification Apparatuses, Processes and Systems (“NBSA”) transforms authenticating NFT generation input, NFT authentication input, document publishing input, NFT document access input datastructure/inputs via NBSA components into authenticating NFT generation output, NFT authentication output, document publishing output, NFT document access output outputs. A document publishing request datastructure structured to specify a set of document info fields associated with a document is obtained. A hash of the set of document info fields is generated. A document object associated with the document is stored. A document publishing transaction structured to facilitate storing publication information regarding the document is submitted to a blockchain. An NFT metadata datastructure structured to specify the document identifier and an identifier of the document publishing transaction is generated. A set of subscribers for the document is determined. For each respective subscriber, a notification NFT is minted and a subscriber notification message is sent.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
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 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
74.
NFT Based Secure Authentication and Notification Apparatuses, Processes and Systems
The NFT Based Secure Authentication and Notification Apparatuses, Processes and Systems (“NBSA”) transforms authenticating NFT generation input, NFT authentication input, document publishing input, NFT document access input datastructure/inputs via NBSA components into authenticating NFT generation output, NFT authentication output, document publishing output, NFT document access output outputs. An NFT document access request datastructure is obtained. An owner blockchain address is determined. Authorization data is evaluated. An NFT metadata datastructure associated with a notification NFT identifier is obtained. A document publishing transaction identifier associated with the notification NFT identifier is determined. A first document hash specified via a document publishing transaction is determined. A second document hash associated with a document object corresponding to a document object identifier specified via the document publishing transaction is determined. Match between the first document hash and the second document hash is verified. A document corresponding to the document object is provided to a subscriber.
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
G06Q 20/36 - Architectures, schémas ou protocoles de paiement caractérisés par l'emploi de dispositifs spécifiques utilisant des portefeuilles électroniques ou coffres-forts électroniques
H04L 9/00 - Dispositions pour les communications secrètes ou protégéesProtocoles réseaux de sécurité
75.
Blockchain Augmented Crypto Asset Valuation Apparatuses, Processes and Systems
The Blockchain Augmented Crypto Asset Valuation Apparatuses, Processes and Systems (“NBSA”) transforms authenticating NFT generation input, NFT authentication input, document publishing input, NFT document access input, transfer transaction input, clawback transaction input, valuation access request datastructure/inputs via NBSA components into authenticating NFT generation output, NFT authentication output, document publishing output, NFT document access output, transfer transaction output, clawback transaction output, valuation access response outputs. A crypto asset valuation request datastructure is obtained. A relevant crypto asset valuation transaction for a crypto asset is determined. Historical crypto asset valuation data is retrieved from a blockchain. A default valuation, a higher band valuation and a lower band valuation of the crypto asset are computed by AI crypto asset valuation engines. A valuation of the crypto asset computed by a best performing AI crypto asset valuation engine is selected. A crypto asset valuation transaction for the crypto asset is submitted to the blockchain.
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
76.
Transfer Transaction Blockchain with Clawback Apparatuses, Processes and Systems
The Transfer Transaction Blockchain with Clawback Apparatuses, Processes and Systems (“NBSA”) transforms authenticating NFT generation input, NFT authentication input, document publishing input, NFT document access input, transfer transaction input, clawback transaction input datastructure/inputs via NBSA components into authenticating NFT generation output, NFT authentication output, document publishing output, NFT document access output, transfer transaction output, clawback transaction output outputs. A transfer transaction processing request datastructure structured as specifying a transaction requestor blockchain address, a transfer transaction identifier, and authorization data is obtained. The authorization data is evaluated to verify control over the transaction requestor blockchain address. A clawback post transaction is submitted to a blockchain. A clawback post transaction notification is sent to a transfer transaction handling smart contract that validates the clawback post transaction by checking compliance with a set of predefined clawback rules, and transfers cryptographic assets to sender of a transfer transaction associated with the transfer transaction identifier.
The NFT Based Secure Authentication and Notification Apparatuses, Processes and Systems (“NBSA”) transforms authenticating NFT generation input, NFT authentication input, document publishing input, NFT document access input datastructure/inputs via NBSA components into authenticating NFT generation output, NFT authentication output, document publishing output, NFT document access output outputs. An authenticating NFT generation request datastructure structured to specify a set of source asset identifiers and an owner blockchain address is obtained. For each respective source asset identifier, source asset data associated with the respective source asset identifier is obtained, a hash of the source asset data is generated, and a source asset object associated with the respective source asset identifier is stored in an adjunct repository. A master hash is generated from the generated hashes. An NFT metadata datastructure structured to specify the master hash and a link to each source asset object is generated. An authenticating NFT is minted.
G06Q 20/38 - Protocoles de paiementArchitectures, schémas ou protocoles de paiement leurs détails
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
78.
Automatic release preparation and deployment for software applications
Methods and apparatuses are described for automatic release preparation and deployment for software applications. A server generates a candidate release build of selected software applications to be deployed to a production computing environment, including: building application artifacts associated with the applications and storing the application artifacts in a repository, updating a project configuration file associated with the applications, and creating a release branch associated with the applications. The server deploys the application artifacts of the candidate release build into a functional acceptance test computing environment and validates operation of the application artifacts. The server promotes the application artifacts to a performance acceptance test computing environment and validates operation of the application artifacts in the performance acceptance test computing environment The server promotes the application artifacts to a production computing environment when operation of the application artifacts is validated in the performance acceptance test computing environment.
A computer-implemented method is provided for quantitative performance evaluation of a call agent. The method comprises converting an audio recording of a call between the call agent and a customer to a text-based transcript and identifying at least one topic for categorizing the transcript. The method also includes retrieving a set of criteria associated with the topic. Each criterion correlates to a set of predefined questions for interrogating the transcript to evaluate the performance of the call agent with respect to the corresponding criterion. Each question captures a sub-criterion under the corresponding criterion. The method further includes inputting the predefined questions and the transcript into a trained large language model to obtain scores for respective ones of the predefined questions. Each score measures a degree of satisfaction of the performance of the call agent during the call with respect to the sub-criterion captured by the corresponding predefined question.
09 - Appareils et instruments scientifiques et électriques
36 - Services financiers, assurances et affaires immobilières
Produits et services
Downloadable software in the nature of a mobile spatial application for investment services, namely, securities brokerage and electronic trading of securities Investment services, namely, securities brokerage and electronic trading of securities
81.
SYSTEMS AND METHODS FOR IDENTIFYING UNREGISTERED CONSUMERS OF WEBSERVICES
Computerized systems and methods are provided for identifying connection between at least one application in a set of client applications within a multi-tenant network and a service application hosted on a server. Audit logs are generated that track activities for respective ones of the client applications over a predetermined duration. Information from a first audit message of each client application is extracted that includes an audit identification and a connecting IP address associated with the corresponding client application. Information from a second audit message of each client application is extracted that includes an audit identification and a process identification of the corresponding client application. The extracted information is used to identify one or more client applications as being connected to and consuming the service application.
Methods and apparatuses are described for automated customer engagement prediction and classification. A server generates a feature vector comprising variables corresponding to historical user activity data for a user. The server encodes, for each feature vector, each variable in the feature vector into a corresponding weight-of-evidence value. The server transforms each encoded feature vector into an embedding in a multidimensional vector space. The server generates, for each user, a user engagement probability value by identifying embeddings of other users in proximity to the user embedding using a similarity measure and determining an engagement outcome for the identified embeddings. The server assigns each user to an engagement probability cluster based upon the engagement probability value for the user. The server generates instructions for a remote device to initiate communications to each user based upon the assigned engagement probability cluster.
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
09 - Appareils et instruments scientifiques et électriques
16 - Papier, carton et produits en ces matières
36 - Services financiers, assurances et affaires immobilières
41 - Éducation, divertissements, activités sportives et culturelles
Produits et services
Providing referral services in the field of investment advice and financial planning; Providing business information to financial service providers by means of an Internet web site, in the field of business marketing; consulting services in the field of marketing financial services; marketing services rendered to members of the financial services industry, namely, business marketing consulting services, creating and designing promotional materials for use by financial service providers and assisting financial service providers with implementing their own direct mail campaigns, and developing advertising campaigns and public relations campaigns; personnel placement and recruiting services; promoting public awareness of the need for investment planning. Downloadable computer software applications for managing investment portfolios; downloadable computer software applications used by financial service providers for contact management; downloadable computer software applications for initiating, processing and tracking financial transactions; computer software for portfolio modeling; downloadable computer software applications for maintaining, managing and reporting financial information; downloadable computer software applications for use by financial service providers to obtain investment transaction and account information; downloadable computer software applications for use in obtaining access to, and enhancing the user's experience of, an Internet web site which provides news, information and online financial services. Printed booklets Booklets and brochures in the field of investments and financial services. Providing financial investment information services to individuals providing personalized investment information by electronic mail; Providing financial information services, namely, to agency services in the field of securities; financial administration of retirement plans administration services; providing financial information in the field of retirement planning; real estate investment services; mutual fund financial information provided by electronic means; Providing financial advisory services, namely, money management; Financial administration of employee benefit plans concerning insurance and finance, defined employee benefit plans concerning insurance and finance, defined contribution plans in the nature of retirement plans and employee pension plans; Mutual fund investment services; providing retirement plan sponsors with financial news and information, information about retirement planning, investment account information, and information about mutual fund performance; financial administration and investment management services rendered to non-profit organizations; electronic bill payment services; financial administration of credit card accounts; financial analysis; donor advised investment of funds for charitable purposes; Financial risk management services; charitable fundraising services; financial services rendered primarily to states, municipalities and tax exempt organizations, namely, providing financial news and information and investment account information by means of the Internet; real estate management services; providing financial information by electronic means; Financial consulting services rendered to employers with respect to the design and administration of employee benefit plans concerning insurance and finance; financial market information services, namely, compiling, analyzing and providing information regarding securities; investment management in the field of private placement of securities; providing research in the field of investments and finance; Providing financial information services relating to the transition from work to retirement or from one job to another; automated mutual fund brokerage clearinghouse services and mutual fund custody services; investment management services; providing financial information about employee stock option plans to participants and potential participants in such plans; financial and actuarial consulting services; insurance brokerage services; financial services, namely, compiling and analyzing, organizing being financial consulting, managing and reporting in the nature of providing user specific financial information by means of the Internet, in the field of investment accounts, bank accounts, credit card accounts, frequent flyer award accounts and other personal financial data; consulting services in the field of insurance; financial planning; investment advice in the field of retirement; retirement fund investment services; investment management in the field of initial public offerings; providing an online computer database featuring financial information of general interest to investors; securities brokerage services; Providing financial investment information services to individuals relating to personalized investment information, investment account management and securities brokerage services, all by means of wireless communication devices and by means of the Internet; Financial administration of stock option plans, employer stock purchase plans and directed share programs for others; life insurance and annuity underwriting services; securities brokerage services provided to holders of stock options; automated securities trade execution services; providing online computer database in the field of securities prices information; electric fund transfer services; loan financing. Providing information in the field of financial education to financial service providers by means of an Internet web site; Education and entertainment services, namely, a web-based non-downloadable continuing video series featuring financial education and insights specific to the Latino Community; arranging and conducting online workshops in the field of investments and financial planning; providing online newsletters in the field of investments, finance and related subjects; Educational services, namely, conducting classes, workshops, seminars and conferences in the field of investments and in the field of marketing financial services; and distributing course materials in connection therewith.
84.
Automatic data-driven optimization of a target outcome using machine learning
Methods and apparatuses are described for automatic data-driven optimization of a target outcome using machine learning. A server generates a first feature dataset and applies a trained outcome prediction model to the first feature dataset as input to generate a second feature data set and a first predicted value for a target outcome. The server displays the first predicted value on a client device. The server receives input corresponding to one or more preferences or constraints from the client device and adjusts the trained outcome prediction model based upon the received input to incorporate the one or more preferences or constraints. The server applies the adjusted outcome prediction to the second feature dataset as input to generate a third feature data set a second predicted value for the target outcome. The server displays the second predicted value on the client device.
A method for automatically connecting a computing device to one of a first virtual private network (VPN) and a second VPN over a network includes receiving, by the computing device from a server system over the network, availability indicia. The method also includes obtaining, by the computing device, a priority status indicating one of a high priority and a low priority. The method further includes determining, by the computing device, a connection VPN selected from the group consisting of the first VPN and the second VPN, the determination based on at least one of the availability indicia and the priority status of the computing device. The method includes establishing, by the computing device over the network, a connection to the connection VPN. The first VPN is prioritized over the second VPN.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software using artificial intelligence for review and approval of electronic communications; Downloadable computer software that uses artificial intelligence models to quickly scan, score and analyze electronic communications and generates a risk analysis report based on analyzed data; Downloadable computer software, accessible via application programming interfaces (APIs), for review and approval of electronic communications. Providing temporary use of non-downloadable computer software using artificial intelligence for review and approval of electronic communications; Providing temporary use of online non-downloadable computer software that uses artificial intelligence models to quickly scan, score and analyze electronic communications and generates a risk analysis report based on analyzed data; Providing temporary use of online non-downloadable computer software, accessible via application programming interfaces (APIs), for review and approval of electronic communications.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software using artificial intelligence for review and approval of electronic communications; Downloadable computer software that uses artificial intelligence models to quickly scan, score and analyze electronic communications and generates a risk analysis report based on analyzed data; Downloadable computer software, accessible via application programming interfaces (APIs), for review and approval of electronic communications. Providing temporary use of non-downloadable computer software using artificial intelligence for review and approval of electronic communications; Providing temporary use of online non-downloadable computer software that uses artificial intelligence models to quickly scan, score and analyze electronic communications and generates a risk analysis report based on analyzed data; Providing temporary use of online non-downloadable computer software, accessible via application programming interfaces (APIs), for review and approval of electronic communications.
Methods and apparatuses are described for intent-aware virtual assistant chat routing. A server receives a request from a user of a client device to transfer a chat-based communication session from a virtual assistant application to an agent. The server captures a topic value and a user message from the chat-based session. The server identifies a user intent associated with the user message by applying a trained intent classification model. When a user intent is identified, the server selects an agent to receive the chat-based session based upon the user intent and a complexity value associated with the user intent and connects an agent device associated with the selected agent to the chat-based session. When a user intent is not identified, the server selects an agent to receive the chat-based session based upon the topic value and connects an agent computing device associated with the selected agent to the chat-based session.
G06Q 30/015 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance
G06F 40/40 - Traitement ou traduction du langage naturel
H04L 51/02 - 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 en utilisant des réactions automatiques ou la délégation par l’utilisateur, p. ex. des réponses automatiques ou des messages générés par un agent conversationnel
H04L 51/04 - Messagerie en temps réel ou quasi en temps réel, p. ex. messagerie instantanée [IM]
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Software as a service (SAAS) featuring software for use in business and financial risk management, namely regulatory compliance, financial crimes compliance, business intelligence, market and collateral risk management, identity management, personnel screening and background investigations, fraud prevention and detection, regulatory compliance analytics, customer due diligence, third- and fourth-party risk management, corporate protective intelligence, hospitality, and travel safety.
90.
DIGITAL CONTENT CLASSIFICATION AND RECOMMENDATION USING CONSTRAINT-BASED PREDICTIVE MACHINE LEARNING
Methods and apparatuses are described for digital content classification and recommendation using constraint-based predictive machine learning. A server trains a machine learning (ML) recommendation model to generate digital content layouts each comprising digital content item slots arranged according to one or more digital content selection constraints. The server receives user profile information for a first user. The server executes the trained ML recommendation model to generate a plurality of digital content item displays, each including a selected digital content item placed in each slot. The server determines, for each digital content item display, an interaction prediction score for each digital content item in the display. The server selects a digital content item display based upon the interaction predictions scores. The server transmits the selected digital content item display to a client device.
Methods and apparatuses are described for provisioning and managing data orchestration platforms in a cloud computing environment. A server provisions in a first region a first data orchestration platform comprising (i) a first data transformation instance, (ii) first endpoints, and (iii) a first data integration instance. The server provisions in a second region a second data orchestration platform comprising (i) a second data transformation instance, (ii) second endpoints, and (iii) a second data integration instance. The server integrates the first data integration instance and the second data integration instance with an identity authentication service. The server monitors operational status of the first orchestration platform and the second orchestration platform using a monitoring service. The server refreshes virtual computing resources in each of the first orchestration platform and the second orchestration platform using a rehydration service.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 8/71 - Gestion de versions Gestion de configuration
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
H04L 41/0806 - Réglages de configuration pour la configuration initiale ou l’approvisionnement, p. ex. prêt à l’emploi [plug-and-play]
H04L 41/50 - Gestion des services réseau, p. ex. en assurant une bonne réalisation du service conformément aux accords
H04L 41/5054 - Déploiement automatique des services déclenchés par le gestionnaire de service, p. ex. la mise en œuvre du service par configuration automatique des composants réseau
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software using artificial intelligence for review and approval of public communications; Downloadable computer software that uses artificial intelligence models to quickly scan, score and analyze sales brochures, fact sheets, infographics, whitepapers, financial reports, flyers and social media content, and generates a risk analysis report based on analyzed data; Downloadable computer software, accessible via application programming interfaces (APIs), for review and approval of communications and documents. Providing temporary use of online non-downloadable computer software using artificial intelligence for review and approval of public communications; Providing temporary use of online non-downloadable computer software that uses artificial intelligence models to quickly scan, score and analyze sales brochures, fact sheets, infographics, whitepapers, financial reports, flyers and social media content, and generates a risk analysis report based on analyzed data; Providing temporary use of online non-downloadable computer software, accessible via application programming interfaces (APIs), for review and approval of communications and documents; Software as a service (SAAS) featuring software for use in business and financial risk management, namely regulatory compliance, financial crimes compliance, business intelligence, market and collateral risk management, identity management, personnel screening and background investigations, fraud prevention and detection, regulatory compliance analytics, customer due diligence, third- and fourth-party risk management, corporate protective intelligence, hospitality, and travel safety.
93.
Workforce management in an agile development environment
Methods and apparatuses are described for workforce management in an Agile development environment. A server retrieves data from software development workforce applications, including Agile data. The server creates an Agile organization hierarchy data structure using the retrieved data. The Agile organization hierarchy data structure comprises developer nodes; developer position nodes; team structure nodes; project domain nodes; and business unit nodes. Each node is connected to other nodes in the data structure. The server generates, for display on a client device, a user interface comprising the Agile organization hierarchy data structure. The server determines adjustments to the Agile organization hierarchy data structure based upon input received from the client device. The server updates a connection between nodes in the Agile organization hierarchy data structure based upon the determined adjustments. The server transmits the updated Agile organization hierarchy data structure to the client device for display.
Methods and apparatuses are described for automated latency-aware purging of database records. A server determines a synchronization latency between a storage database and an online transaction processing (OLTP) database. When the synchronization latency is below a predetermined threshold, the server identifies a first database object in the OLTP database and selects database records to be purged from the first database object based upon a data purge instruction set. The server identifies a second database object in the storage database that corresponds to the first database object and selects database records in the second database object based upon the data purge instruction set. The server purges the database records from the first database object in the OLTP database when a characteristic of the database records to be purged from the first database object matches a characteristic of the database records selected in the second database object.
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 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p. ex. des interruptions ou des opérations d'entrée–sortie
A computer-implemented method is provided for recommending at least one pertinent electronic document for supporting a call between a customer and an agent. The method includes converting in real time content of the call between the customer and the agent from speech to digitized text, isolating a predefined number of words in the digitized text of the converted call content as the call is in progress and converting the predefined number of words in text to a phoneme sequence. The method also includes identifying at least one probable business category associated with the phoneme sequence and detecting sections of one or more documents associated with the probable business category that are similar to the content of the call.
36 - Services financiers, assurances et affaires immobilières
41 - Éducation, divertissements, activités sportives et culturelles
45 - Services juridiques; services de sécurité; services personnels pour individus
Produits et services
Providing information in the field of wealth management; Financial advisory services, namely, wealth preservation and intergenerational wealth transfer planning services. Production and distribution of videos in the field of family management and relationships; Providing on-line non-downloadable articles in the field of in the field of family management and relationships; Providing on-line newsletters in the field of family management and relationships; Online publication of blogs in the field of family management and relationships; Education services, namely, providing non-downloadable webinars in the field of family management and relationships; Entertainment services, namely, providing podcasts in the field of family management and relationships; providing in-person learning forums in the field of family management and relationships. Online information services in the field of intrafamily relationships as they related to intergenerational wealth; Providing a website featuring information in the fields of personal relationships and personal relationship communication practices and services.
97.
CAPTURING AND UTILIZING CONTEXT DATA IN CROSS-CHANNEL CONVERSATION SERVICE APPLICATION COMMUNICATION SESSIONS
Methods and apparatuses are described for capturing and utilizing cross-channel context data in conversation service application communication sessions. A computing device establishes a first communication session between a first conversation service application and a first remote device. The orchestration utility detects an intent to transfer the first communication session to a second remote device. The orchestration utility captures context data generated during the first communication session. The computing device establishes a second communication session between a second conversation service application and the second remote computing device. The orchestration utility configures the second communication session based upon the context data, including synchronizing a state of the second communication session to a state of the first communication session.
Techniques are provided for managing and operating a microservices architecture with ad distributed cache. A data provider microservice may modify a data object stored on a database managed by the data provider microservice. In response, the modified data object may be transmitted to the distributed cache for storage. A data consumer microservice may request a data object. The distributed cache may be searched for the requested object. If the requested object is stored at the distributed cache, the requested object may be provided to the data consumer microservice. If the requested object is not stored at the distributed cache, the data consumer microservice may issue a request for the data object to the data provider microservice that manages the database that stores the data object. The data provider microservice may provide the data object to the distributed cache for storage and provide the data object to the data consumer microservice.
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
99.
PREDICTING USER ATTRIBUTES USING UNCERTAINTY ESTIMATE MODELING
Methods and apparatuses are described for predicting user attributes using uncertainty estimate modeling. A server trains a plurality of machine learning (ML) models to predict a distribution of values for a plurality of user attributes. The server determines an uncertainty measure of the ML models for each user attribute based upon the predicted distribution of values. The server receives a request for prediction of user attributes from a client device and generates for each user attribute a first predicted distribution using one or more of the trained models. The server classifies, for each user attribute, an accuracy of the first predicted distribution based upon the uncertainty measure and provides the first predicted distribution and the accuracy for each user attribute to the client device for presentation. The server updates the first predicted value for the user attributes based upon input received from the client computing device.
Methods and apparatuses are described for predicting compliance of text documents with a ruleset using self-supervised machine learning. A server executes an NLP teacher model on first unlabeled sentences to generate a first compliance pseudo-label for each first unlabeled sentence. The server trains an NLP student model using the first unlabeled sentences and first compliance pseudo-labels, including injecting input noise by aggregating each unlabeled sentence with one or more sentences adjacent to each unlabeled sentence into a sentence block and providing the aggregated sentence blocks as input to train the NLP student model. The server executes the trained NLP student model, using second unlabeled sentences, to generate a second compliance pseudo-label for each second unlabeled sentence. The server determines compliance of the second sentences with one or more rulesets using the second compliance pseudo-labels.
