22 results about "Rdf graph" patented technology

The invention relates to a large language model driven virtual knowledge graph automatic construction method based on a mapping mode, and the method comprises the following steps: 1, extracting database table structure metadata and a constraint relation, and converting a database mode into a graph structure based on an RDF standard; 2, converting the mapping modes into query statements conforming to SPARQL grammar, querying RDF graph structures corresponding to the database modes, and obtaining extraction results of the mapping modes; step 3, based on the semantic coding model and the generative large language model, aligning the database table structure metadata and the constraint relationship into the ontology vocabulary, and obtaining an alignment result and an alignment confidence from the database to the ontology; and 4, according to a mapping mode extraction result and an alignment result from the database to the ontology, performing ontology expansion and virtual knowledge graph mapping construction based on the alignment confidence. According to the method, the virtual knowledge graph construction process can be automated, the ontology structure can be expanded according to needs, and resource consumption in the construction process is reduced.

Methods, systems, and apparatuses are configured to generate new industrial asset models that can be efficiently queried. The new industrial asset models can be tailored to specific users and represented in an RDF knowledge graph. In particular, the RDF graph can define variables that correspond to OPC variables. The RDF knowledge graph queried via a query that is compliant with a GraphQL API.

The invention belongs to the technical field of intelligent models, and particularly relates to a bridge management and maintenance knowledge graph representation method based on a large language model collaborative graph neural network, which comprises the following steps: S1, converting an OWL ontology into a knowledge graph RDF graph of a triple, generating a plurality of sub-graphs with different relationships according to a preset migration scheme, and turning to S2; s3, adopting a preset hybrid walk strategy, starting from a plurality of entities of each sub-graph, generating an entity sequence based on a specific step number, and turning to S3; constructing an inverse relation and a self-loop relation on the basis of the initial RDF graph to form a new RDF graph, and turning to S4; and S5, carrying out splicing and feature conversion on the local structure embedding, the semantic embedding and the global structure embedding obtained in the steps S2-S4 to obtain an embedded representation of the fused entity and relationship. According to the method, complex semantic information, text information and structure information in the OWL ontology can be fully utilized, automatic completion and link prediction of knowledge are realized, and the accuracy and integrity of the bridge management and maintenance knowledge graph are improved.

This provides a computer implementation method for executing linearly recursive queries on an RDF (Resource Description Framework) graph database using a query engine. [Solution] The method includes the steps of: obtaining a first part of a query that defines one or more initial conditions for query elements in a second part of a query on an RDF graph database as input; and obtaining at least two clauses that specify that the second part of the query is executed recursively. The first clause defines how the output of the execution of the second part of the query is used as input for the next execution of the second part of the query. The second clause includes query elements that define the second part of the query and describe how the output of the execution is queried using (i) one or more initial conditions as input for the first execution or (ii) the output of the previous execution for the next execution.

The invention provides a SPARQL query optimization method and system in a parallel computing environment, and belongs to the technical field of RDF query optimization. According to the scheme, a candidate edge set corresponding to a first query edge of a query graph structure is split, task decomposition optimization is carried out, semantic independence of parallel tasks is achieved, and dependence blocking in traditional pipeline parallelism is avoided; meanwhile, according to the scheme, query semantics are fused into locality sensitive Hash design for the first time, the attribute neighborhood similarity of candidate edges is effectively quantified by constructing a Hash sketch vector comprising query attribute constraints, and task-level redundancy calculation elimination is achieved; according to the scheme, redundant calculation in the query process is remarkably reduced, and the query efficiency of the large-scale RDF graph is effectively improved; meanwhile, according to the scheme, the worst-case optimal connection characteristic of the Generaic Join algorithm is combined with parallel task decomposition for the first time, an execution normal form of vertex-by-vertex extension according to connected subgraphs is provided, and the performance bottleneck of a traditional algorithm in a large-scale RDF graph is broken through.

A computer-implemented method for generating by a query engine a graph of operators for a SPARQL query over an RDF graph. The method includes obtaining a graph of operators executable by the query engine, the graph comprising a plurality of basic operators, at least two of said operators being of a first type each configured to find RDF triples of the RDF graph that match a respective basic graph pattern. The method further comprises identifying a group of operators among the at least two basic operators of the graph which are of the first type. The respective basic graph patterns of the group of operators have same subject and / or predicate and / or object and the identified group of operators is replaced in the graph by an equivalent operator configured to find RDF triples of the RDF graph that match the respective basic graph patterns of the group of operators.

The application discloses a kind of based on ontology organization method of knowledge graph, belong to knowledge graph technical field.First, element ontology structure and ontology element knowledge graph structure are defined;Through big language model and rdflib library, the entity data information of RDF graph model is extracted and is converted into triple, is stored and forms the structured data layer of knowledge graph, selects core element entity, the name, definition structure feature and graph structure feature are vectorized and the similarity of core entity pair is calculated, traverses and merges entity pair, based on entity pair, the most authoritative value of core element entity node is calculated.The application realizes ontology fine-grained organization and cross ontology accurate alignment by analyzing ontology semantic element, effectively improves the automation degree and accuracy of ontology organization process.

Techniques are provided for generating and maintaining Precomputed Result Tables ("PRTs") that are used by a database server to improve performance of SPARQL queries that target an RDF graph set. Each PRT corresponds to a particular pattern, which may be simple-triple, star, or chain. The techniques support the creation of PRTs for chain patterns that contain multiple instances of the same property, and PRTs for star and chain patterns that include reverse properties. Techniques are also described for maintaining such PRTs as Data Manipulation Language (DML) operations make changes to the RDF graph tables that belong to the RDF graph set associated with the PRTs.

The invention discloses a bridge knowledge graph multi-task embedded representation learning method under a complex semantic mode, and the method comprises the steps: inputting a to-be-processed OWL body into a pre-training model which is finely adjusted in advance for coding, and obtaining an entity embedded representation and a relation embedded representation of the OWL body; executing a corresponding prediction task as the input of the multi-task prediction model to obtain a prediction result; the pre-training model fine tuning process comprises the steps of mapping an OWL into an RDF map, generating a multi-view corpus according to a specific relation in a migration mode, and training a model through an MLM task after semantic enhancement. According to the method, through ontology mapping conversion and multi-semantic view division, semantic enhancement is performed by using a specific method according to the characteristics of each view, and complex semantic information is fully utilized to encode the OWL ontology to obtain entity and relationship embedding representation, so that the core problems of insufficient semantic information utilization and logic loss in a traditional method are effectively solved.

The invention relates to a computer-implemented method for updating a virtual RDF graph database. The method comprises the following steps of: providing file storage which has durability D in ACID attributes and ensures consistent writing; providing a virtual RDF graph database including a first RDF graph database updatable by the stream and a second read-only RDF graph database stored on the file store and updated in batches; a directory is provided for storing metadata describing a second read only (RDF) graph database on a file store, the directory conforming to the ACID. The method further includes obtaining a tuple stream and a batch of tuples, applying the tuple stream to the first RDF graph database, applying the batch of tuples to the second RDF graph database by calculating a snapshot of the second RDF graph database, the snapshot including the batch of tuples, calculating a sequence of concurrency control operations appropriately performed by using consistent writes stored by the file to ensure ACID attributes of the snapshot; storing the computed snapshot on a file store; and registering the computed snapshot in the directory, thereby obtaining an updated description of the virtual RDF graph database.

To provide a computer-implemented method, a data structure, and an apparatus (120) for providing and / or storing change history of a first knowledge graph (102).SOLUTION: An apparatus (120) includes at least one memory (112), particularly a non-volatile memory. A second knowledge graph (104) including at least part of a first knowledge graph (102) is stored in the at least one memory (112). The second knowledge graph (104) includes change history. The change history includes at least one triplet including the triplet of the first knowledge graph (102) as a subject. At least one triplet includes a predicate and an object, and the predicate and the object link the triplet of the first knowledge graph (102) with a subgraph of the second knowledge graph (104) that includes information about changes made in the first knowledge graph (102), in particular an RDF graph of the second knowledge graph.SELECTED DRAWING: Figure 1

The invention relates to the technical field of data modeling, and discloses a dynamic modeling method and device based on an RDF graph, computer equipment and a medium, and the method comprises the steps: setting object types and relation types corresponding to different business scenes; obtaining a plurality of entities in an actual business scene and a relationship among the entities, defining each entity as an object, and obtaining a plurality of objects and a relationship among the objects; matching a corresponding object type and a relationship type based on the relationship between each object and the object in the actual business scene, and instantiating each object attribute and an attribute value corresponding to each attribute based on the object type; and constructing a data model based on the RDF graph based on the object type, the relationship type, the plurality of objects, the relationship between the objects, the object attributes and the attribute value corresponding to each attribute of the actual business scene. The method is not limited by a traditional relational database, and data modeling can be achieved without tedious data table structure and code modification.

Techniques are provided for generating and maintaining Precomputed Result Tables ("PRTs") that are used by a database server to improve performance of SPARQL queries that target an RDF graph set. Each PRT corresponds to a particular pattern, which may be simple-triple, star, or chain. The techniques support the creation of PRTs for chain patterns that contain multiple instances of the same property, and PRTs for star and chain patterns that include reverse properties. Techniques are also described for maintaining such PRTs as Data Manipulation Language (DML) operations make changes to the RDF graph tables that belong to the RDF graph set associated with the PRTs.

The invention relates to an industrial ontology matching method and system based on a sum graph isomorphic network, and belongs to the technical field of semantic network and natural language processing. The method comprises the following steps: firstly, inputting an ontology file into a model, and generating an RDF graph structure and a semantic embedding vector of each concept; secondly, jointly inputting the semantic embedding vector and the RDF graph structure into a graph isomorphic network model which adopts a multi-head self-attention mechanism to realize inter-node information interaction and structural dependence modeling, and extracting structural features of the graph through message passing and feature aggregation; carrying out fusion and nonlinear transformation on the features of the nodes and the historical states of the nodes, updating the features of the nodes, and generating a structure embedding vector; thirdly, fusing the semantic embedding vector and the structure embedding vector by adopting a gating aggregator to obtain a comprehensive embedding vector; and finally, calculating the similarity between the concepts, and determining an optimal matching relationship. According to the method, the problem that the isomorphic invariance of the graph cannot be ensured by a traditional method is solved, and the matching accuracy is improved.

The present invention discloses a knowledge graph semantic place retrieval method and device based on Skyline. The user inputs the user's location, queries keywords, and returns the required number of places k; extracts the coordinate information contained in the place entity in the RDF graph, constructs an R‑tree index and a place keyword set, and generates a word vector set; returns the Top‑k places according to the proposed Skyline-based semantic place retrieval algorithm. The present invention proposes to use keyword fuzzy matching to replace the precise matching method in the traditional knowledge graph spatial data retrieval method, which can provide users with more potential choices; proposes a semantic place retrieval algorithm based on Skyline, which solves the extreme value problem caused by the Top‑k linear sorting function in the traditional method, achieves a balance between the two dimensions of spatial distance and semantic relevance, and improves the retrieval efficiency.

Techniques are provided for generating and maintaining pre-computed result tables ("PRTs") used by a database server to improve performance of SPARQL queries targeting RDF graph sets. Each PRT corresponds to a particular pattern, which can be a simple triple, a star, or a chain. The techniques support creating PRTs for chain patterns containing multiple instances of the same property, as well as creating PRTs for star and chain patterns that include inverse properties. Techniques are also described for maintaining such PRTs when data manipulation language (DML) operations make changes to tables belonging to RDF graphs of a RDF graph set associated with a PRT.

A Linked Data Hypergraph (LDH) System and method that serializes RDF data in a plurality of triples where some of the plurality of triples form two-triple hyperedges with a hypernode as common node in either the triple subject or triple object position. The LDH system and method using a Linked Data Hypergraph Ontology (LDHO) enables an improved query and modeling of digital twin objects through space-time. The LDH system operates using an RDF graph database having a plurality of named graphs each serializing a digital twin of an object and wherein each named graph and each serialized digital twin has a URI associated therewith and a Linked Data Hypergraph Awareness (LDHA) configured to use the LDHO specifications to transform each of the serialized digital twins into a digital twin model when loaded, perform inference, and respond to queries with answers returned in RDF Linked Data.

A computer-implemented method that validates SHACL graphs on RDF graphs within a relational database system. SHACL graphs include shape-target pairs, where the shape represents a constraint a node must satisfy, and the target specifies which node to validate. RDF graphs consist of RDF terms, represented as nodes (subject, predicate, object) using IRIs, literals, or blank node identifiers. Each node is associated with a unique identifier, and relationships are stored in a relational database. The method compiles SHACL graphs into SQL expressions by converting them into negation normal form, applying negations to atomic constraints, and translating these into SQL using a lookup table. Validation is performed by executing SQL expressions on the database, ensuring each node satisfies the SHACL constraints.

Techniques are provided for generating and maintaining Precomputed Result Tables (“PRTs”) that are used by a database server to improve performance of SPARQL queries that target an RDF graph set. Each PRT corresponds to a particular pattern, which may be simple-triple, star, or chain. The techniques support the creation of PRTs for chain patterns that contain multiple instances of the same property, and PRTs for star and chain patterns that include reverse properties. Techniques are also described for maintaining such PRTs as Data Manipulation Language (DML) operations make changes to the RDF graph tables that belong to the RDF graph set associated with the PRTs.

The invention relates to data security, in particular to a method and a system for selectively disclosing verifiable certificates based on associated data, which are used for solving the problems that the selective calculation amount of the existing verifiable certificates is large, the efficiency is low, the relationship among attributes in the certificates cannot be reflected for a plurality of certificates, and a user is not constrained. According to the scheme, under the framework of the RDF graph, the attributes in the voucher are represented by triples, and a monotone expansion scheme and a linear secret sharing scheme are used for efficiently restraining the attributes which can be selectively disclosed by a user, so that malicious behaviors of the user are prevented; according to the method and the device, attributes in a single voucher can be selectively disclosed, and attribute information association can be carried out after selective disclosure of a plurality of vouchers, so that effective combination of the vouchers can be realized, and meanings to be expressed by the disclosed information can be accurately and efficiently transmitted to a verification party. On the basis, signatures of a plurality of vouchers are aggregated into a BLS signature, so that the purpose of combining the vouchers is achieved.

The application discloses a kind of based on knowledge graph's ontology modeling method of flower disease and insect pest.The ontology modeling method constructs the ontology model capable of meeting the basic requirements of flower disease and insect pest control by studying field-related literature, compared with other existing ontology, additionally considers the influence of environment on flower disease and insect pest control, environmental factors for the prevention and treatment of flower disease and insect pest not only focus on treatment, more focus on prevention, timely prevention and treatment of disease and insect pest can further reduce the damage of flower.Using RDF graph to store ontology structure, according to the self-defined RDF2PG mapping method, the extracted triples are not stored in Neo4j database according to the structure of ontology model without other storage methods, which standardizes the managed knowledge, improves the storage efficiency and automatic construction of atlas ability.

The invention discloses an ontology organization method based on a knowledge graph, and belongs to the technical field of knowledge graphs. Firstly, an element ontology structure and an ontology element knowledge graph structure are defined; constructing an RDF graph model for the literature class ontology and the OWL class ontology through a large language model and an rdflib library, extracting entity data information, converting the entity data information into a triple, storing and forming a structured data layer of a knowledge graph, selecting core element entities, vectorizing names, definition structural features and graph structural features of the core element entities, and calculating similarity to obtain core entity pairs; and traversing and merging the entity pairs, and calculating a final authority value of the entity node of the core element based on the entity pairs. According to the method, the ontology semantic elements are analyzed, so that ontology fine-grained organization and cross-ontology accurate alignment is realized, and the automation degree and accuracy of the ontology organization process are effectively improved.