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Distributed knowledge graph query method and device and storage medium

A knowledge map and query method technology, applied in the field of distributed knowledge map query methods, devices and storage media, can solve problems such as lack of parallelism, huge knowledge map merging results, large amount of data transmission overhead, etc., to achieve high query efficiency and connection The full effect of the process

Pending Publication Date: 2022-03-08
HUNAN UNIV
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  • Application Information

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Problems solved by technology

The problem with these methods lies in two points. ①The result of knowledge graph merging is huge, far exceeding the final result itself. The distributed merging stage will bring a lot of data transmission overhead; does not implement good parallelism

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  • Distributed knowledge graph query method and device and storage medium
  • Distributed knowledge graph query method and device and storage medium
  • Distributed knowledge graph query method and device and storage medium

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Embodiment Construction

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them.

[0048]With the development of the Internet, massive amounts of data are emerging rapidly and complicated. In this context, a model that can express a large amount of complex data more flexibly—Resource Description Framework (RDF) emerged as the times require. The RDF data model was proposed by W3C, which provides a unified standard to represent things, that is, uses triple sets to describe resources on the Web and the relationship between resources. The triplet is the basic unit of knowledge representation in the knowledge map, and each piece of knowledge constitutes the knowledge map, which drives the management of knowledge in the form of a map, and realizes knowledge data modelin...

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Abstract

The invention provides a distributed knowledge graph query method and related equipment. The query efficiency of distributed knowledge graph query can be improved. The method comprises the steps that a first device obtains a target query statement input by a user; the first device processes the target query statement to obtain a target query graph; the first device performs linear segmentation on the target query graph to obtain N query sub-trees; the first device allocates the N query sub-trees to a plurality of second devices, so that the second devices perform retrieval filtering from a database according to a target query sub-tree to obtain a target candidate result set, and obtain corresponding matched candidate result sets from the plurality of second devices corresponding to the first device according to the target candidate result set, matching the first candidate result set with the matching candidate result set to obtain a pairing result, and returning the pairing result; and the first device merges and connects the pairing results corresponding to each second device in the plurality of second devices to obtain a final result set.

Description

【Technical field】 [0001] The present application belongs to the field of query, and in particular relates to a distributed knowledge map query method, device and storage medium. 【Background technique】 [0002] The query requirements of knowledge graphs have important practical significance. Existing knowledge retrieval methods focus on querying based on keywords, and keyword queries often lack important structural information in semantics, such as searching for "hometown is in Fujian and works in Hunan". "People" in the form of keywords are "hometown", "Fujian", "Hunan", "work", "personnel" and so on as queries; where the relationship loss between different keywords introduces an inevitable ambiguity, such as The above keyword set can also be interpreted as "personnel whose hometown is in Hunan and works in Fujian", which caused an actual error. The query of the knowledge graph not only focuses on the content of keywords, but also focuses on the logical association and inte...

Claims

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Application Information

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IPC IPC(8): G06F16/36G06F16/332
CPCG06F16/367G06F16/3329
Inventor 李友焕石沛凡袁知秋
Owner HUNAN UNIV
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