Knowledge-driven SPARQL query construction method

A construction method and knowledge-driven technology, applied in the field of data query, can solve the problems of large storage space, long running time, and time-consuming, etc., and achieve the effects of reducing search space, accurate screening, and reducing running time

Active Publication Date: 2019-07-09
智言科技(深圳)有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] (1) The search space is large, and entities and predicates need to be fully arranged. The search space will increase exponentially with the increase of the number of entities and predicates, which will consume

Method used

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  • Knowledge-driven SPARQL query construction method
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  • Knowledge-driven SPARQL query construction method

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Embodiment Construction

[0050] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0051] Such as figure 1 As shown, the present embodiment relates to a knowledge-driven SPARQL query construction method, and the main steps of the method are as follows:

[0052] 1) Obtain the SPARQL query statement submitted by the user, and extract the entity set and predicate set in the SPARQL query statement;

[0053] 2) Determine the entity set and predicate set in step 1), if only one predicate is included in the predicate set, and only one entity is included in the entity set, then the SPARQL query statement is classified as a simple question;

[0054] 3) Judging the entity set and predicate set in step 1), if only one predicate is included in the predicate set, and only two entities are included in the entity set, then the SPARQL query statement is classified as a factual problem;

[0055] 4) Judging the predicate set in step 1), if...

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Abstract

The invention discloses a knowledge-driven SPARQL query construction method, and belongs to the technical field of data query. The method comprises the following steps of obtaining an SPARQL query statement submitted by a user, and extracting an entity set and a predicate set in the SPARQL query statement; analyzing and judging respectively, entity numbers and predicate numbers in an entity set and a predicate set, classifying query statements into simple questions, fact questions and complex questions respectively, dividing the complex questions into display entity questions and implicit entity questions, constructing query processes for different categories of questions respectively, and corresponding query answers are obtained. According to different problems, a corresponding knowledgegraph is constructed, and correct SPARQL query statements are screened out. The search space of a traditional method is reduced, and the operation time is shortened. When a complex problem is processed, if the implicit entity does not appear, the implicit entity is limited through an intermediate product, so that a correct SPARQL query statement is found out, and a result is executed accurately and quickly.

Description

technical field [0001] The invention relates to the technical field of data query, in particular to a knowledge-driven SPARQL query construction method. Background technique [0002] In the prior art, the traditional data query component method is mainly to arrange and combine the entities and predicates in the results of entity links and relationship links by violence, and then filter the constructed SPARQL query statements through some simple filtering rules. Due to the characteristics of SPARQL syntax, each SPARQL is composed of several triples, and each triple has two entity placeholders and one predicate placeholder. It is an item to exhaustively enumerate all the combinations Things with a lot of work. For example, from the question "List TV shows with producer as Erik Bork and company is Dream Works Television?", the entity set E can be extracted: [0003] {<http: / / dbpedia.org / resource / Erik_Bork>, [0004] <http: / / dbpedia.org / resource / DreamWorks_Television...

Claims

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Application Information

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IPC IPC(8): G06F16/332G06F16/36
CPCY02D10/00
Inventor 周柳阳张美郑卫国
Owner 智言科技(深圳)有限公司
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