114 results about "Entity identifier" patented technology

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.

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.

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.

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.

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.

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 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.

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.

An entity data store contains electronic records associated with entities (e.g., businesses). For each entity, electronic records include an entity identifier, entity operational data, and parameters associated with that entity (e.g., business name, address, etc.). A resolution rule library contains electronic records associated with resolution rules, including a rule identifier and rule logic. An ingestion engine of a computer server receives big data input and accesses the resolution rule library. Based on resolution rule logic and the received big data input, the computer server automatically resolves that two electronic records with different entity identifiers are associated with a single entity. The computer server can then update the entity data store to reflect information for a resolved single entity identifier and automatically execute an enterprise workflow for a risk relationship between the enterprise and the entity represented by the resolved single entity identifier.

A machine implemented method includes sensing entities in first and second domains. If a first stimulus is present and an entity is in the first domain, the entity is transferred from first to second domain via a bridge. If a second stimulus is present and an entity is in the second domain, the entity is transferred from second first domain via the bridge. At least some of the first domain is outputted. An apparatus includes a processor that defines first and second domains and a bridge that enables transfer of entities between domains, an entity identifier that identifies entities in the domains, a stimulus identifier that identifies stimuli, and a display that outputs at least some of the first domain. The processor transfers entities from first to second domain responsive to a first stimulus, and transfers entities from second to first domain responsive to a second stimulus.

A method includes sensing entities in first and second domains. If a first stimulus is present and an entity is in the first domain, the entity is transferred from first to second domain via a bridge. If a second stimulus is present and an entity is in the second domain, the entity is transferred from second first domain via the bridge. At least some of the first domain is outputted. An apparatus includes a processor that defines first and second domains and a bridge that enables transfer of entities between domains, an entity identifier that identifies entities in the domains, a stimulus identifier that identifies stimuli, and a display that outputs at least some of the first domain. The processor transfers entities from first to second domain responsive to a first stimulus, and transfers entities from second to first domain responsive to a second stimulus.

The application belongs to the technical field of data cleaning and integration, and specifically provides a method for efficiently cleaning and integrating massive data by using artificial intelligence technology, which mainly comprises the following steps: acquiring multi-source data, the multi-source data containing entity identifiers, attribute identifiers and attribute values; extracting original data from the multi-source data according to preset entity identifiers; associating each piece of original data with a blood relationship record, the blood relationship record containing a generation path description of the original data; taking the original data as nodes, establishing edges between the nodes based on the generation path description, and constructing a data blood relationship network; and extracting nodes from the blood relationship network as a candidate node set according to preset attribute identifiers. The application realizes accurate tracing of the data generation and circulation process, improves the comprehensiveness and accuracy of data credibility evaluation, guarantees the accuracy of the integration result of the target entity attribute, and provides reliable data support for subsequent analysis and decision-making based on the integrated data.

This invention discloses a multimodal experimental data extraction method and system with an embedded intelligent agent search mechanism, relating to the field of data extraction technology. The method includes: performing multimodal parsing on input target documents, identifying multimodal regions and constructing a source data index system; identifying research objects in the target documents and mapping synonymous expressions to entity identifiers; invoking multiple data extraction agents of different modalities to perform parallel data extraction on the target documents; performing cross-modal alignment on triplet data, detecting and arbitrating data conflicts, determining data truth values ​​and performing reverse source tracing verification, and generating structured knowledge base entries. This invention solves the technical problems of low experimental data extraction efficiency and difficulty in collaborative analysis and conflict detection of multi-source heterogeneous data in existing technologies, leading to low accuracy of the constructed knowledge base. It achieves the technical effects of improving the accuracy and reliability of data extraction, realizing intelligent fusion verification of cross-modal information, and ensuring data traceability.

The invention belongs to the technical field of network security and security operation, and relates to a hidden attack detection method and system based on UEBA and AI agents, and the method comprises the steps: carrying out the analysis, mapping, time sequence correction and entity disambiguation of multi-source behavior data and security event data, and obtaining a standardized event containing a unified entity identifier and a unified time identifier; establishing a behavior baseline based on the standardized event, and performing abnormal detection to generate an alarm containing risk grading and evidence identification; the evidence block vectors are put into a database, and context evidences are retrieved under the constraint of entities and time; time sequence data and a knowledge graph are constructed based on the context, and a candidate attack chain is searched; the AI intelligent experience certificate generates a certificate chain update risk and outputs a disposal judgment; and the processing and certification chain feedback attribution is used for updating the baseline, and detection, retrieval and chain scoring rules are carried out. According to the technical scheme, the hidden attack research and judgment basis stability and the disposal decision consistency can be improved, and the reliability and traceability of detection and verification are enhanced.

The application provides a financial data correlation network dynamic construction method and system for double-library collaborative processing, solves the problems of low efficiency of multi-hop traversal query of a relational database in financial correlation query, high coupling degree of an independent graph database and a system in related technologies, and difficulty in data synchronization. The application obtains a target entity identifier, a relationship type and a traversal depth by analyzing a query request; performs correlation topology retrieval in a graph database to obtain a correlation entity identifier set and a path topology; performs attribute retrieval in a relational database by taking the correlation entity identifier set as a batch query condition to obtain complete attribute data of an entity; and fuses the path topology and the complete attribute data of the entity to output a structured result. The application realizes the collaboration of transaction capability of the relational database and efficient traversal capability of the graph database by decoupling topology traversal and attribute retrieval, and improves the dynamic construction and query efficiency of the financial correlation network.

Embodiments of the present application disclose a place retrieval method, an electronic device and a storage medium, comprising: obtaining a to-be-retrieved text; performing entity segmentation on the to-be-retrieved text to obtain at least one entity corresponding to the to-be-retrieved text; determining an entity identifier corresponding to each entity in the to-be-retrieved text according to a preset association relationship; and outputting a target place corresponding to the to-be-retrieved text based on the entity identifier corresponding to each entity and an identifier type corresponding to the entity identifier. The scheme can not only improve the recalled places during place retrieval, but also improve the accuracy of place retrieval.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a cross-channel multi-modal data alignment and fusion method, device, equipment and medium. And executing probability time alignment based on the time probability distribution to generate a time alignment feature sequence, completing entity recognition and alignment by using the time alignment feature sequence to generate a unified entity identifier, constructing a multi-modal association graph based on the time alignment feature sequence and the unified entity identifier, and aggregating node features to generate a unified fusion representation vector. Through probability time alignment, entity unified identifier generation and graph structure aggregation, automatic alignment and fusion of cross-channel multi-modal data are realized, the association expression ability of heterogeneous data in a complex business scene is enhanced, and the robustness and analysis precision of a fusion result are improved.