Mapping knowledge domain embedding method for fusing multiple background knowledge

A technology of background knowledge and knowledge graph, applied in special data processing applications, instruments, unstructured text data retrieval, etc., can solve inappropriate problems

Active Publication Date: 2017-11-24
RENMIN UNIVERSITY OF CHINA
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Problems solved by technology

However, existing methods simply link structured knowledge and textual knowledge together, which is very inappropriate

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  • Mapping knowledge domain embedding method for fusing multiple background knowledge
  • Mapping knowledge domain embedding method for fusing multiple background knowledge
  • Mapping knowledge domain embedding method for fusing multiple background knowledge

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Embodiment Construction

[0039] Aiming at the problem of entity weak description knowledge, the present invention adopts MCK to assist KG embedding. MCK includes description knowledge and supplementary knowledge. Among them, description knowledge, in the task, those entity description information in KG are preprocessed and more than 3 words and average The description information is 69 words in length, and the longest description does not exceed 343 words. Set to null if there is no descriptive knowledge; supplementary knowledge, for each entity, the supplementary knowledge is sentences highly related to the entity extracted from a text corpus, such as Wikipedia. In the task of the present invention, the external knowledge of each entity consists of approximately 40 sentences. The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments.

[0040] The meanings of symbols involved in the present invention are shown in the following table:

[004...

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Abstract

The invention relates to a mapping knowledge domain embedding method for fusing multiple background knowledge. The method includes the steps of firstly, selecting high-quality entity depiction information from entity labels of a knowledge base and selecting high-quality linguistic data related to an entity from Web linguistic data to establish the MCK (multiple background knowledge); secondly, learning the embedding expression of the knowledge base by embedding the MCK; thirdly, obtaining a semantic embedding vector of the corresponding entity from the MCK through a DBALSTM model, wherein DBALSTM represents depth D, bidirectional B, attention A and base LSTM; fourthly, completing the mapping knowledge domain embedding for the fusing multiple background knowledge by using a fusing embedding mechanism for the fine grit combination of three-element groups MCK and RDF. The accuracy of mapping knowledge domain embedding can be improved.

Description

technical field [0001] The invention relates to a knowledge map embedding method, in particular to a knowledge map embedding method that integrates multi-background knowledge. Background technique [0002] In recent years, the construction of web-scale knowledge graphs (knowledge graphs, KG) is increasing day by day, and using KG to solve practical problems such as DBPedia, Wikidata, Freebase, YAGO and Probase is widely used in natural language question answering, intelligent search, and knowledge reasoning, fusion and complementation. congruent. However, as the size of KG increases, graph-represented KG is facing the problem of data sparsity and computational inefficiency in its application. More importantly, the graph-represented KG is not convenient for machine learning, which is an indispensable tool for big data automation and intelligence. For this reason, KG's embedded representation learning technology was born and became the mainstream, which is to project entitie...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/30G06F16/367
Inventor 孟小峰杜治娟
Owner RENMIN UNIVERSITY OF CHINA
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