156 results about "Entity identifier" patented technology

Guiding query creation for a generative artificial intelligence (AI)-enabled assistant, including: receiving, via a natural language interface for a security framework monitoring a cloud deployment, a natural language input comprising one or more entity identifiers; gathering information based on the one or more entity identifiers; providing, to a generative artificial intelligence (AI) model, a prompt based on the natural language input and comprising the gathered information; and receiving, from the generative AI model, a response to the prompt.

The invention discloses a false information multi-source association reasoning system based on a knowledge graph, and the system comprises a data collection and standardization module which is used for carrying out the multi-source collection and duplicate removal of a text, and generating a structured input data set; the semantic extraction and normalization module is used for executing alias merging and disambiguation and outputting a semantic extraction result; the entity alignment module is used for cross-platform entity matching and confidence evaluation, entity identification unification and attribute and alias merging; the graph construction and anchor point module is used for constructing a fact graph and a traceability graph; the candidate constraint generation module is used for forming a candidate constraint set based on the multi-source evidence statistics support degree; the space-time constraint and weight reduction module is used for executing path consistency and joint constraint according to Allen and RCC8 to obtain an updated evidence weight result; and the evidence chain and pushing module is used for enumerating and scoring the evidence chain and pushing the evidence chain through an external interface. According to the invention, false information multi-source association reasoning is realized.

The invention discloses a knowledge base retrieval method fused with a natural language large model, and relates to the technical field of artificial intelligence. Comprising the following steps that 1, a knowledge representation structure is constructed, and the knowledge representation structure comprises a knowledge base hypergraph based on knowledge fragments, entity identifiers and theme tags and a dense vector index recording dense vectors of the knowledge fragments; 2, analyzing an original natural language query input by a user, and performing matching in the knowledge base hypergraph based on the original natural language query to obtain an initial node set; 3, on the knowledge base hypergraph, determining a candidate knowledge fragment set and a corresponding multi-view local semantic abstract; and 4, calling the natural language large model, and generating a retrieval answer based on the target knowledge fragment set. According to the method, the accuracy, coverage and interpretability of knowledge retrieval can be remarkably improved.

An entity-level privacy system receives a query directed towards a shared dataset, the shared dataset comprising one or more data entries associated with one or more distinct entities, each entity of the one or more distinct entities being identifiable by one or more unique entity identifiers. The entity-level privacy system implements an entity-level privacy constraint, the entity-level privacy constraint comprising a dynamic aggregation constraint based on the one or more unique entity identifiers. The entity-level privacy system determines that the one or more unique entity identifiers satisfy a threshold condition comprising a minimum number of entities. The entity-level privacy system enforces the entity-level privacy constraint on the query and generates an output to the query based on the entity-level privacy constraint and the dynamic aggregation constraint while maintaining entity-level privacy associated with the one or more distinct entities.

Systems, methods, and other embodiments associated with a framework for multi-entity detection, data sourcing, and processing are described. In one embodiment, a multi-entity processing method includes parsing an electronic document being processed in a processing flow for a first entity to detect that the document also concerns a second entity based on entity identifiers in the document. In response to the detection, the method determines an inter-entity agreement that governs processing between the first entity and second entity by matching attributes of the document against stored agreement data structures. The method automatically orchestrates processing of an inter-entity transaction between the first entity and the second entity by generating execution steps according to sequential and parallel dependencies specified by the inter-entity agreement. And, the method generates electronic records in a system of the first entity and a system of the second entity that reflect execution of the inter-entity transaction.

Various embodiments of the present disclosure provide a user interface and a natural language interface for predictive models. The techniques may include receiving a user interface application programming interface (API) request that indicates an entity feature dataset associated with the entity identifier and / or an event progression model, receiving a model API request via a conversational user interface comprising a natural language query for interacting with the event progression model, receiving a simulated event risk data object for the entity identifier that is generated using the entity feature dataset, the event progression model, and the natural language query, and initiating a rendering of an event progression graphical visualization via the conversational user interface that is based on the simulated event risk data object.

Systems and methods for securely managing digital assets and generating immutable transaction records linked to decentralized identifiers (DIDs). A processing system operating within a distributed ledger technology (DLT) network receives digital asset transaction requests including entity identifiers associated with unique DIDs. The processing system establishes cryptographically secured connections with digital wallets corresponding to these entity identifiers, retrieves digital asset balances from a distributed ledger—including non-transferable cryptographic tokens linked to the DIDs—and executes smart contracts to cryptographically modify digital asset balances. Immutable transaction records comprising timestamps, cryptographic hashes linked to DIDs, and event reference identifiers are generated and stored within the distributed ledger, preserving cryptographic integrity. Authorized access to these immutable records is governed by access permissions encoded in the executed smart contracts, enhancing security, transparency, and compliance in decentralized digital asset management.

The invention provides an electronic archive processing method and device based on multi-modal data. The method comprises the following steps: acquiring normalized electronic archive data in a current period; performing layout analysis on the electronic archive data, and identifying text information of the electronic archive data; utilizing a natural language processing model to extract entities and corresponding business elements in the text information; matching the entity with an existing entity in a stored electronic archive knowledge graph, and determining a unique entity identifier; based on the semantic features of the electronic archive data, the business elements and the text information, determining semantic relationships among different electronic archives; updating the stored electronic archive knowledge graph by taking the unique entity identifier as a node and the semantic relationship as an edge to obtain a new electronic archive knowledge graph; and based on the business elements and the new electronic archive knowledge graph, classifying the electronic archive data to obtain a classification result and corresponding cataloguing information. According to the method, intelligent extraction, semantic association and automatic cataloguing of the electronic archive elements are realized.

A computer implemented method for determining entity attributes. The method comprises determining one or more entity identifiers, determining an entity server address of the entity based on the one or more entity identifiers, wherein the entity server address points to an entity server; verifying the entity server address transmitting a message for request for information to the entity server address, receiving entity information from the entity server; and providing, to a machine learning model, the received entity information. The machine learning model is trained to generate a numerical representations of entities based on the entity information.

Techniques are provided for processing rules expressed in a domain-specific language. A computing system may receive a rule including an entity identifier, a property of the entity, and one or more logical operators delimited by syntactic tokens of the language. The rule is parsed into an abstract syntax tree (AST) representation that structurally represents entities, properties, and conditional logic, and the AST is transformed into an executable function configured to evaluate input data objects defined according to a machine-readable data model. Execution of the function on input data produces a logical outcome along with intermediate results corresponding to evaluations of individual conditions and logical operators. The computing system generates an execution trace comprising the logical outcome and the intermediate results, the trace being stored in a structured log retrievable to provide evidence of how outcomes were determined.

Systems and methods are disclosed for centralized management and application of distributed parameters through a data generation platform. The platform obtains an aggregate rule set including zone-specific parameter sets and zone classifiers for multiple zones, where the rule set determines allocation metric values associated with transaction values of resources. Upon receiving input data including entity identifiers, resource identifiers, and transaction data, the platform maps the data to zones by comparing zone classifiers, filters the aggregate rule set to generate a zone-specific rule subset, and applies the subset to generate allocation metric values. The platform can process requests synchronously through online message queues and / or asynchronously for bulk processing. Machine learning models can use distribution patterns across multiple resource sets to generate overall allocation metrics and modification suggestions. The platform can provide a graphical user interface for displaying allocation metrics, resource information, and / or supplemental explanations.

A policy-governed network resolution system generates a cryptographically verifiable Resolution Receipt (RR) for each identifier request. An identifier (e.g., a domain name under a BEIDNS / BEIDomain / BEITLD namespace) is routed to a resolver gateway, matched to a basepoint within a curated identifier reservoir, evaluated under a versioned policy container, and authorized by a signed scope token to enforce selective disclosure. The resolver may enrich the context with a knowledge-graph entity identifier, derive a decentralized identity root for Behavioral Economics Identity (BEI), and mint a content-addressable global object key. Minute-grade activity is metered and recorded in the RR, including policy version, reason codes, lifecycle state, audit anchors, and a signature chain, further supporting denial receipts with remediation steps. RR digests may be recorded in append-only logs and optionally anchored to a distributed ledger. Aggregated RR metrics may be streamed for real-time indexing, resource governance, and bounded rollback in IoT and real-estate embodiments.

A computer-implemented method for identifying a product citation in a document, the method comprising searching, in the document, for an entity identifier corresponding to an entity and, if an instance of the entity identifier is detected in the document, determining a portion of the document around the instance of the entity identifier as a target text, wherein the entity is associated with a product catalogue, the product catalogue comprising a plurality of product identifiers; applying a first regular expression to the target text, wherein the first regular expression is configured to match one or more of the plurality of product identifiers; and if a product identifier from the plurality of product identifiers is determined to be cited in the target text, adding an entry to a citation database linking the document and the product identifier.

Systems and methods are presented herein for selectively preventing display of brand and business identifiers in content that is considered offensive, objectionable, disturbing, and / or unsettling, to prevent an unintended association by viewers of the content between the content and the brand or business. A request to display media content, comprising at least one frame with objectionable subject matter, is received. In response to determining the at least one frame comprises objectionable subject matter, a determination is made as to whether an entity identifier is visible in the at least one frame. In response to determining at least one entity identifier is visible in the at least one frame, a first context of the objectionable subject matter and a second context of the entity identifier are determined. The first context is compared to the second context and, based on the comparing, a masking action is determined to be required for the entity identifier.

The application belongs to the field of network security operation, and particularly relates to a network security alarm accurate identification and grading method based on AI.The method is connected with multiple types of security systems to collect alarms and context data, generate a unique alarm identifier and an entity identifier set, and construct an alarm entity graph through entity disambiguation alignment;secondly, multi-dimensional deep features such as time sequence self-excitation and topological persistence are extracted, normalized and spliced into feature objects and stored in a feature warehouse;then, corresponding data is obtained through a normal behavior self-supervision and attack technology identification double-track model, and a true alarm probability is calculated through an evidence ratio fusion model;and finally, alarm dynamic grading and differentiated disposal are realized based on attack features and risk budget.The application reduces the alarm false alarm rate, solves the problem of disposal resource mismatch, and enhances the security operation efficiency.

The application discloses an intelligent agent generated interactive system and method applied to hospital operation management, relates to the technical field of hospital operation management, and captures each interactive operation of a user for an operation entity from a hospital heterogeneous system and records each operation as an atomic interactive event; analyzes the atomic interactive event to generate a user long-term preference vector and stores the user long-term preference vector; when a natural language query is received, a target operation entity identifier and an analysis index are analyzed; the analyzed index is matched with a candidate analysis model, an execution model is generated, and an index analysis result set is output; the data type and the dimension quantity of the index analysis result set are analyzed, and a basic UI component requirement is generated; the UI component requirement and a UI component preference are fused and decided, a target UI component selection is generated, and a final interactive interface is rendered and generated; and the frequency distribution is updated according to the user interaction. Personalized decision is supported, and the use experience of the user is improved.

The invention relates to an engineering data management method, device and equipment and a storage medium, and the method comprises the steps: collecting an engineering entity identifier and monitoring data of an engineering site for unit construction, and forming a basic data unit; performing entity information detection on the component identifier in the basic data unit and a pre-constructed engineering knowledge graph, and when it is detected that the component identifier is not matched with information of the engineering knowledge graph, extracting entity information corresponding to the component identifier, and performing engineering node construction and relation updating on the engineering knowledge graph according to the entity information, generating an updated knowledge graph, performing detection again until matching succeeds, and generating an engineering data unit. According to the method, the data unit is verified in real time through the quality rule based on the knowledge graph, and the abnormal data is automatically corrected by adopting a strategy polling mechanism, so that the accuracy of data processing and the timeliness of abnormal response are remarkably improved.

The invention discloses a lightweight trusted access method and system based on an entity identifier, and the method comprises the steps: in a one-way authentication mode, an upper computer initiates a lightweight trusted access authentication request based on the entity identifier to an industrial controller, and the industrial controller receives and verifies an upper computer entity identifier and signature voucher information carried in the request; only the legal upper computer is allowed to be connected with the industrial controller to obtain the control service; in the bidirectional authentication mode, the upper computer initiates a lightweight trusted access authentication request based on an entity identifier to the industrial controller, and the industrial controller verifies the entity identifier and signature voucher information of the upper computer carried in the request; the industrial controller sends a lightweight trusted access authentication request based on the entity identifier to the upper computer, and the upper computer verifies the industrial controller entity identifier and signature voucher information carried in the authentication request; and only the legal devices passing the bidirectional authentication are allowed to be connected with each other and execute the control service. The application can ensure that the industrial control equipment safely accesses the system to execute the industrial control service.

The invention is a cryptographic pseudonym mapping method for an anonymous data sharing system, the method being adapted for generating pseudonymised data from entity data originating from data sources (DSi), wherein the data are identified at the data sources (DSi) by entity identifiers (D) of the respective entities, and wherein the pseudonymised data are identified by pseudonyms assigned to the respective entity identifiers (D) applying a one-to-one mapping. Furthermore, the invention is a computer system implementing the method, and a computer program and a computer-readable medium.

Systems, computer program products, and methods are described herein for generating an interactive 3D environment using spatial computing to generate historical digital components. The present invention is configured to identify a user account(s), wherein the user account(s) is associated with a resource account(s); identify a resource transmission(s) associated with the resource account(s), wherein the resource transmission(s) is associated with a geolocation coordinate(s) or an entity identifier(s); generate a virtual computing environment based on the at least one resource transmission and geolocation coordinate(s) or the entity identifier(s); generate a virtual computing environment avatar based on the user account, the resource transmission(s) and the geolocation coordinate(s) or the entity identifier(s); and generate a resource transmission movie in the virtual computing environment, wherein the resource transmission movie comprises at least one virtual computing environment component based on the resource transmission(s).

The application discloses a natural language graph query generation method based on a knowledge hypergraph, performs semantic analysis and entity standardization on an input natural language query to obtain standard entity identifiers involved in the query; takes the standard entity identifiers as anchor points to extract a local hyper-subgraph containing semantic hyper-edges and associated entity nodes from the knowledge hypergraph, wherein the semantic hyper-edges are used to express a complex semantic association involving multiple entities, roles and constraints; performs structured decomposition on the natural language query to generate multiple sub-questions with semantic boundaries, and maps each sub-question to one or a group of the semantic hyper-edges, while constructing a directed dependency relationship between the sub-questions; and the application aims to solve the problem of how to accurately identify and express the nested dependency relationship between multiple entities, roles and constraints in the natural language query while preserving the complete semantic structure of the natural language query, and ensure that the dependency can be completely transmitted and verified in a structured manner.

A first network signal is received indicating a device identifier in response to a transaction involving an electronic device uniquely associated with the device identifier. An entity identifier specific to an entity associated with the transaction is determined. In response to an initialization event of the electronic device, a second network signal from the electronic device is received that identifies the electronic device. In response to the second network signal, a configuration is communicated to the electronic device that is specific to the entity associated with the transaction.

Methods, apparatuses, or computer program products that provide data access authentication for a data partition based on encrypted context associated with a data access request for the data partition. In some examples, a data access request to access data within a partition is received. In some examples, the data access request is associated with an encrypted context for a requesting entity identifier associated with the data access request. In some examples, a partition identifier and an encrypted partition key for the partition are identified based on the data access request. Additionally, a candidate validation partition key for the partition is generated based on the encrypted partition key, the encrypted context, and the partition identifier. In some examples, the candidate validation partition key is validated based on a comparison between the candidate validation partition key and a validation partition key associated with the partition to facilitate processing the data access request.

This application relates to a method, system, device, and medium for real-time evaluation of business rules based on a large language model. The method includes: invoking a large language model to convert natural language business rules into structured description data containing entity identifiers, attribute identifiers, and rule constraints; mapping entity identifiers and attribute identifiers to the location information of corresponding program elements in a domain model based on a pre-stored mapping library, generating detailed mapping data; generating source code files implementing a preset evaluator interface based on the structured description data and the detailed mapping data; converting the source code files into an executable form and executing them in an isolated execution environment; invoking the evaluator interface, evaluating the execution results using generated test cases, and generating a verification report. This application achieves fully automated conversion of business rules to executable code, reducing maintenance costs and improving the efficiency of rule deployment.

A computer-implemented method for resource requirement forecasting in a RAN is disclosed The method comprises extracting a RAN static entity identifier value from RAN raw data, and extracting at least one feature value from the RAN raw data depending on a selected type of a machine-learning system. Upon determining that the extracted RAN static entity identifier value is not yet represented in a first data structure associated with a current time slot, the method comprise adding a representation of the extracted RAN static entity identifier value to the first probabilistic data structure associated with a current time slot. Additionally, the method comprises storing a representation of the extracted RAN static entity identifier value to a second data structure for the current time slot and feeding the at least one extracted feature value as input value to a machine-learning system for predicting the selected type of resource optimization.

The present application provides a method, apparatus, device, and medium for determining entity triples in asset custody. The method relates to the field of financial technology or other related fields, including: a candidate triple includes a candidate entity identifier and a candidate entity relationship; at least one of a preset pronoun library, a preset entity identifier library, and a preset entity identifier classification strategy is sequentially used to determine the candidate entity identifier as a target entity identifier; the preset entity identifier library is an identifier library that receives new preset entity identifiers related to asset custody in real time; in response to the candidate entity identifier being the target entity identifier, the candidate entity relationship is sequentially determined as the target entity relationship using at least one of a preset entity relationship library and a preset entity relationship classification strategy; the preset entity relationship library is a relationship library that receives new preset entity relationships related to asset custody in real time; in response to the candidate entity relationship being the target entity relationship, the candidate triple is determined to be the target triple.

The invention relates to an intelligent information auxiliary input method and system, which are used for improving the automatic complementation and entity recognition capability in a structured data input process. According to the system, a real-time input stream is constructed through character-by-character input of a user, input content is converted into a vector sequence through a keyword generation module, and fuzzy matching is completed based on an improved tree structure. By introducing an automaton state transition mechanism and combining a path editing distance and a semantic tag, candidate entries with high matching degree are screened out. And the candidate result is compared and identified with a database standard name through the entity mapping module to form a target entity identifier, and finally, the target entity identifier is sorted and displayed according to a multi-dimensional index. The method has the capabilities of character-level association, semantic constraint matching and path consistency judgment, and the accuracy and efficiency of structured input can be remarkably improved.

The invention provides an intraoperative demanded instrument recognition method and system based on semantic recognition, and relates to the technical field of data processing. The method comprises the following steps: acquiring voice information of a surgeon; converting the voice information into statement information; performing preprocessing including grammar error correction on the statement information to eliminate grammar errors of the statement information; constructing a dual-task model comprising a BERT module, an NER module with a rule filter unit and an identifier identification module; training the double-task model in combination with a Bayesian algorithm improved based on a probability model so as to complete hyper-parameter optimization of the double-task model; inputting the preprocessed statement information into the trained dual-task model, and outputting a target entity identifier of the instrument required by the surgeon; and activating corresponding indication equipment according to the target entity identifier, and indicating the required instrument. The intention of a surgeon can be automatically and accurately identified, and indication of required medical instruments is completed.

This invention discloses a cross-platform business system integration method based on knowledge graphs, comprising the following steps: S1, reading data from the business platform database and generating field text, entity identifiers, and relation records; S2, inputting the field text into an ALBERT model, generating field semantic vectors through a domain word vector gating layer; S3, forming triples based on entity identifiers and relation records and writing them into the knowledge graph; S4, inputting the triples into a TransH model, generating entity structure embedding vectors through dynamic rotation of relation vectors and hyperplane normal vectors; S5, generating entity embedding vectors based on field semantic vectors and entity structure embedding vectors; S6, calculating various distances based on entity embedding vectors to obtain the similarity of cross-platform candidate entity pairs; S7, performing duplicate entity determination on the similarity and updating the knowledge graph. This invention achieves accurate alignment of cross-platform business entities, improves data fusion efficiency and consistency, and is suitable for multi-source business integration scenarios.

The invention provides a data processing method of an industrial database, and relates to the technical field of data processing. The data processing method of the industrial database comprises the following steps: S1, constructing a stream batch integrated processing engine, and carrying out joint calculation on real-time data stream and historical data; s2, dynamically allocating a storage structure according to an entity identifier by adopting an entity partition storage model; s3, executing real-time query based on an incremental graph traversal technology, and dynamically pruning in a traversal process; s4, entity behavior abnormity is detected in real time through the space-time fusion model; and S5, compressing the event stream data according to a causal rule. According to the technology, real-time and historical data are processed by utilizing a stream batch integrated engine, and full-dimension rapid decision analysis is realized. Incremental graph traversal, space-time fusion anomaly detection and the like respectively improve the query efficiency and accurately position faults. The expenditure is reduced through causal rule compression and the like, the end-to-end credibility is guaranteed through the quaternion metadata block and verification technology, the storage read-write efficiency is improved through thermal scheduling, and the problems of response, detection and storage are solved.