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Method for extracting non-taxonomy relations between entities for Chinese patents

A non-categorical relationship and entity technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as semantic irrelevance

Inactive Publication Date: 2016-06-15
BEIJING INFORMATION SCI & TECH UNIV +1
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  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In the research on the extraction of SAO structural relationships in the Chinese patent field, traditional rule-based and machine learning methods cannot effectively solve the problem that the extracted relationship instances structurally meet the requirements of SAO relationships, but have no semantic relationship.

Method used

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  • Method for extracting non-taxonomy relations between entities for Chinese patents
  • Method for extracting non-taxonomy relations between entities for Chinese patents
  • Method for extracting non-taxonomy relations between entities for Chinese patents

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Embodiment Construction

[0064] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0065] Such as figure 1 As shown, a method for extracting non-categorical relations between entities for Chinese patents includes a training process and a testing process. Both the training process and the testing process include the following steps:

[0066] Step 1): Initialize the basic relationship set where the concept pair is located;

[0067] Step 2): automatically mark candidate relational words using a relational word tagging algorithm based on domain relationship strength;

[0068] Among them, domain relationship strength DRV (DomainRelationValue) indicates the strength of the instance re...

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Abstract

The invention relates to a method for extracting non-taxonomy relations between entities for Chinese patents. The method comprises following steps: S1): initializing basic relation sets of concept pairs; S2): automatically marking candidate relational words by use of a relational word marking algorithm based on domain relation intensity; S3): performing characteristic selection to obtain characteristic vectors; S4): performing classification to the characteristic data obtained in S3) by use of a support vector machine SVM. According to the invention, the extraction of non-taxonomy relations between entities for Chinese patents is defined as extraction of relations between entities which suit a SAO structure; a method of syntactic analysis characteristics and relational word dictionary characteristics in combination with traditional characteristics is brought forward, and a support vector machine is used for relation extraction so that the problem of right relation example structures with semantic errors in SAO structure relation extraction task is solved; the method is prior to traditional relation extraction method and can better satisfy practical application needs.

Description

technical field [0001] The invention belongs to the technical field of extracting non-classified relations between entities in Chinese patents, and in particular relates to a method for extracting non-classified relations between entities oriented to Chinese patents. Background technique [0002] The main tasks of ontology learning are concept acquisition and relation extraction. Among them, relation extraction is further divided into classification relation extraction and non-classification relation extraction. The classification relationship refers to the superordinate relationship between concepts, such as China and the country, China is the subordinate concept of the country, and the country is the superordinate concept. Relationships other than categorical relationships are non-categorical relationships, such as causal relationships, domain-specific relationships, sequence relationships, etc. The domain-specific relationship is the main relationship in the non-classif...

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Application Information

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IPC IPC(8): G06K9/62G06F17/27
CPCG06F40/211G06F40/247G06F18/2411
Inventor 吕学强徐丽萍董志安
Owner BEIJING INFORMATION SCI & TECH UNIV
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