Graph model filtering method fusing shallow semantic information

A semantic information and filtering method technology, applied in the direction of semantic tool creation, digital data information retrieval, special data processing applications, etc., can solve problems such as inaccurate acquisition of entity references

Active Publication Date: 2020-07-17
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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  • Abstract
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AI Technical Summary

Problems solved by technology

[0011] In step 1, there are often abbreviations and aliases for entity references, which lead to inaccurate acquisition of entity references

Method used

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  • Graph model filtering method fusing shallow semantic information
  • Graph model filtering method fusing shallow semantic information
  • Graph model filtering method fusing shallow semantic information

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Embodiment Construction

[0025] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them.

[0026] Such as figure 1 As shown, the present invention proposes a graph model filtering method that fuses shallow semantic information, and the method includes the following steps:

[0027] In step 1, there are often abbreviations and aliases for entity references, which lead to inaccurate acquisition of entity references. In the present invention, the Chinese designation is first input into three candidate designation expansion methods: substring expansion, translation expansion, and special abbreviation expansion to obtain accurate and complete entity designation.

[0028] Step 2 Put the obtained accurate and complete entity references into the Chines...

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Abstract

The invention provides a graph model filtering method fusing shallow semantic information, and the method comprises the steps: inputting a Chinese reference into a reference extension method, and obtaining an accurate and complete entity reference; putting the entity reference as a key field of wiki search into a Chinese Wikipedia knowledge base to obtain a candidate entity list of the entity reference; inputting the candidate entity list into a graph model filtering method fusing shallow semantic information to obtain a filtered candidate entity list; and storing the filtered candidate entitylist into a database to prepare for an entity disambiguation module. According to the method, the text similarity is obtained by fusing the shallow semantic information to calculate the context similarity between the candidate entity and the entity reference, and is used as the weight factor of the filtering algorithm; and candidate entity relevancy is calculated based on a graph model in-out degree algorithm to serve as a weight factor of a filtering algorithm, and finally, two weight factors are fused to obtain a comprehensive score to arrange candidate entities, so that entity disambiguation errors are reduced.

Description

technical field [0001] The invention relates to the technical field of entity linking, in particular to a graph model filtering method for fusing shallow semantic information. Background technique [0002] In the era of big data, text resources are an important way for people to obtain information. However, due to the widespread occurrence of polysemy and polysemy in natural language processing, how to make machines understand the ambiguity and diversity of entities, and accurately Providing users with search content is one of the most urgent problems in natural language processing. [0003] Entity linking processes various unstructured / semi-structured inputs, uses multiple techniques, extracts various types of entities, and integrates this information with existing knowledge graphs. [0004] Assuming a given piece of text (such as "Apple launched a new programming language Swift for developers at the conference in San Francisco"), an entity linking system includes the foll...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/35G06F16/335G06F16/36
CPCG06F16/35G06F16/335G06F16/367Y02D10/00
Inventor 贾海涛刘芳李建任利周焕来赫熙煦任金胜许文波
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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