Relationship linking method based on knowledge map

A technology of knowledge graph and relationship, applied in the field of natural language processing, can solve the problem of insufficient link between natural language and knowledge graph, and achieve the effect of reducing the amount of data

Active Publication Date: 2017-12-15
CHONGQING UNIV OF POSTS & TELECOMM
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  • Application Information

AI Technical Summary

Problems solved by technology

An effective solution to the problem of insufficient links between natural language and knowledge graphs is proposed,

Method used

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  • Relationship linking method based on knowledge map
  • Relationship linking method based on knowledge map
  • Relationship linking method based on knowledge map

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Embodiment Construction

[0027] The technical solutions in the embodiments of the present invention will be described clearly and in detail below with reference to the drawings in the embodiments of the present invention. The described embodiments are only some of the embodiments of the invention.

[0028] The technical scheme that the present invention solves the problems of the technologies described above is:

[0029] The main design idea of ​​the technical solution of the present invention is to design an automatic linking algorithm for the relationship in the knowledge map. Use the structured data of the knowledge graph to train a common expression model for a certain relationship. Match and identify these common expressions with unstructured text, and map the successfully matched unstructured text to the corresponding relationship in the knowledge map, so as to realize the relationship link and solve the problem of unstructured natural language text and structured knowledge. The relational map...

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Abstract

The invention relates to a relationship linking method based on a knowledge map. The method comprises the steps that firstly, a ternary group < subject, relation, object > list containing a certain relation is found using a SparQL query statement from a knowledge mapping domain, and a relation text is matched from an unstructured text; a similarity matrix of the relation text is obtained by using an LSWMD algorithm, then clustering is conducted on the relation text by using a density peak clustering algorithm, and a relation text cluster is obtained; the position of all the words in the cluster is extracted based on the relation text cluster, fitting is conducted using the beta distribution, and a word distribution mode of the relation text cluster is obtained; for the candidate relation text of unestablished relation in the unstructured text of an open domain, the vector is constructed using the word distribution mode, a GBDT classifier is used for carrying out the identification, and linking with the knowledge mapping domain is achieved. According to the relationship linking method based on the knowledge map, the problem of insufficient link between a natural language and the knowledge map is effectively solved, and it is helpful for the computer to understand the natural language better.

Description

technical field [0001] The invention belongs to the field of natural language processing, in particular to a method for relational linking based on knowledge graphs. Background technique [0002] Exploring and understanding knowledge on the Internet is one of the long-term goals in the field of artificial intelligence. Due to the emergence of some distributed systems, storing and utilizing data on the Internet is no longer a problem, but it is still a big challenge for computers to understand and use human natural language. The birth of knowledge graph helps computers understand natural language. Knowledge graphs aim to describe various entities or concepts that exist in the real world. Among them, each entity or concept is identified by a globally unique ID, which is called their identifier. Each attribute-value pair is used to describe the intrinsic characteristics of the entity, and the relationship is used to link two entities and describe the relationship between the...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06F17/30
CPCG06F16/355G06F16/367G06F40/211G06F40/30
Inventor 李智星杨茜任诗雅沈柯李苑王国胤胡峰王进雷大江
Owner CHONGQING UNIV OF POSTS & TELECOMM
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