Temporal T-SPARQL query and reasoning method based on Pregel

A reasoning method and temporal technology, applied in other database queries, special data processing applications, and other database retrieval directions, can solve problems such as low query efficiency, achieve good query efficiency, expand query result sets, and improve query efficiency.

Pending Publication Date: 2022-06-24
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

SPARQL query is a combination of a set of tuple patterns, and these tuple patterns are interrelated, so evaluating SPARQL queries in previous relational databases and data parallel systems will have a large number of self-join operations and storage space data redundancy. Query inefficiency

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  • Temporal T-SPARQL query and reasoning method based on Pregel
  • Temporal T-SPARQL query and reasoning method based on Pregel
  • Temporal T-SPARQL query and reasoning method based on Pregel

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Embodiment Construction

[0018] The present invention will be further described below with reference to the accompanying drawings.

[0019] The overall flow of the present invention is as follows figure 1 shown. The sub-module processes it contains are as follows figure 2 , image 3 , Figure 4 , Figure 5 The following describes in detail with reference to each figure. The specific implementation steps are as follows, and the overall process is attached figure 1 .

[0020] 1 Temporal Interval Binary Relation Calculation

[0021] figure 2 Shows the time relationship defined by Allen, and introduces interval unification, which can be used for comparison of temporal connection calculations.

[0022] 2 BSP model

[0023] The Pregel model has the characteristics of parallel computing, batch message, and synchronization mechanism, which enables it to perform parallel processing on the graph with the vertex as the center. The Pregel computing framework is based on an overall synchronous paralle...

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Abstract

The invention discloses a temporal T-SPARQL query and reasoning method based on Pregel. Query processing and optimization are carried out on temporal RDF graph data in a graph parallel computing mode. The research problem can be formally defined as follows: a tense RDF query graph G and a tense query graph Q are given, and all matches of the query graph Q in the data graph G are found out. And converting the T-SPARQL query into a function executed on the vertex, performing communication on the edge by adopting a message passing mode, storing an intermediate result set in a vertex attribute, and performing message aggregation and continuous matching on the basis of the received message in the next round of iteration until the iteration is finished. According to the T-SPGX algorithm, a corresponding query plan is generated according to a given T-SPARQL query, the query plan comprises predicate label matching and time information filtering, and different time filtering methods are adopted for a single tense triple mode and a plurality of tense triple mode connection query. The query efficiency is improved from the aspect of query result optimization, the semantic hierarchy of the tense RDFS is used for reasoning the tense RDF data, an implicit result is reasoned in existing explicit query results, and a query result set is expanded. A universal and extensible solution is provided for the query method of the massive tense RDF data.

Description

technical field [0001] The invention proposes a general and scalable solution for the query method of massive temporal RDF data. A temporal RDF query method based on Pregel is proposed, which can query, process and optimize temporal RDF graph data through graph parallel computing. The research problem can be formally defined as: given a temporal RDF query graph G and a temporal query graph Q, find all matches of the query graph Q in the data graph G. Convert the T-SPARQL query into a function executed on the vertex, communicate on the edge by means of message passing, store the intermediate result set in the vertex attribute, and the next iteration will aggregate the message based on the received message and continue to match until the end of the iteration. It belongs to the field of distributed knowledge semantic query. Background technique [0002] Information in reality naturally has temporal attributes. In order to better represent and manage temporal information, man...

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 贺振宇马宗民
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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