RDF Top-k query method based on neighbor vectors

A query method, rdftop-k technology, applied in the field of RDFTop-k query based on neighbor vectors, can solve problems such as noise

Active Publication Date: 2020-06-19
GUILIN UNIV OF ELECTRONIC TECH
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AI Technical Summary

Problems solved by technology

[0004] Aiming at problems such as noise existing in SPARQL at present, the present invention provides a kind of approximate subgraph matching method based on neighbor vector

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  • RDF Top-k query method based on neighbor vectors
  • RDF Top-k query method based on neighbor vectors
  • RDF Top-k query method based on neighbor vectors

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Embodiment

[0050]A neighbor vector-based RDF query method for querying large-scale RDF data. The method is mainly divided into an offline stage and an online stage. The offline stage mainly includes RDF data preprocessing and index construction. In the online stage, the chi-square value is mainly used to calculate the matching degree of similar nodes, and the extended approximate matching is performed in the form of a tree. Take the set of triples in the RDF data set as an example. The data set of RDF is a set of triples. The query problem conforms to the SPARQL standard, because P is rarely a variable in the actual query problem The situation, so the present invention does not consider the situation that P is a variable, such as figure 1 shown, including the following steps:

[0051] 1) Model RDF data and SPARQL query as directed labeled RDF data graph G and SPARQL query graph Q respectively, use adjacency table to store RDF data graph G and SPARQL query graph Q, and build an inverse ...

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Abstract

The invention discloses an RDF Top-k query method based on neighbor vectors. According to the method, in an offline stage, RDF data and SPARQL query are modeled into an RDF data graph and an SPARQL query graph respectively, and indexes such as an adjacency list, an inverse adjacency list, a label node reverse list index, a node neighbor node label list index, a node h-hop neighbor node set, P-In and P-Out are constructed; in the matching stage, similarity measurement is conducted on the structure of neighbor nodes of candidate nodes and labels of the neighbor nodes based on the chi-square statistics technology, and extension matching is conducted in a spanning tree mode; and finally, obtaining Top-k sequences approximately matched with the SPARQL query graph, and outputting labels of datagraph nodes matched with variable nodes in the SPARQL query graph in each sequence. According to the method, expensive graph isomorphism and editing distance calculation are avoided, high robustness is achieved under the condition that labels and structures are not matched, and SPARQL approximate query questions can be accurately and efficiently answered.

Description

technical field [0001] The invention relates to the technical field of large-scale RDF data query, in particular to a neighbor vector-based RDF Top-k query method. Background technique [0002] Resource Description Framework (RDF) is a framework proposed by W3C to describe information on the World Wide Web, and it provides information description specifications for various applications on the Web. SPARQL is a query language defined by W3C to realize the retrieval standard of RDF data. Many applications generate erroneous data when generating RDF data (such as manual data input introduces errors, etc.), thus causing RDF data to become dirty. In addition, in intelligent question answering scenarios, label noise and structural noise are usually introduced when converting natural language questions raised by users into questions that meet the SPARQL query standard. Execute accurate search for SPARQL queries with noise, it is difficult for the system to find out the answer that...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/901G06F16/903
CPCG06F16/9024G06F16/90335
Inventor 董荣胜刘江江
Owner GUILIN UNIV OF ELECTRONIC TECH
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