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A method for extracting concept of coal mine safety accident ontology

A coal mine security and concept technology, which is applied in other database retrieval, semantic analysis, network data retrieval, etc., can solve problems such as the inability to effectively represent the semantic characteristics and domain characteristics of domain concepts, and affect the extraction effect, so as to improve reusability and improve Good accuracy and performance

Active Publication Date: 2019-01-11
BEIJING INFORMATION SCI & TECH UNIV
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Problems solved by technology

However, the current concept extraction methods cannot effectively represent the rich semantic and domain characteristics of domain concepts, which affects the extraction effect

Method used

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  • A method for extracting concept of coal mine safety accident ontology
  • A method for extracting concept of coal mine safety accident ontology
  • A method for extracting concept of coal mine safety accident ontology

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Embodiment Construction

[0032] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will describe in detail with reference to the drawings and specific embodiments.

[0033] figure 1 It is a schematic flowchart of a method for extracting concepts of coal mine safety accident ontology provided by an embodiment of the present invention. Such as figure 1 As shown, the coal mine safety accident ontology concept extraction method provided by the embodiment of the present invention includes the following steps:

[0034] S101. Crawl text data about coal mine safety accidents from a preset website, where the text data includes training data and test data.

[0035] In the present invention, the preset website may include a coal mine safety network, a coal mine accident network, and a safety management network. The text data can be crawled from these websites by a locomotive crawler tool. The text data may include coal mine...

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Abstract

A method for extracting concept of coal mine safety accident ontology is provided, This method combines a word vector and a conditional random field to extract the concept of coal mine safety accidentontology, fully considers the semantic characteristics and domain characteristics of domain words, and solves the problems of lack of traditional research methods in semantic relationship analysis and inconsistent data management in the field of coal mine safety, and improves the reusability of knowledge. Experiments show that the proposed method improves the precision of concept extraction in the field of coal mine safety compared with the traditional concept extraction method based on CRFs. At the same time, it also proves that the word vector model provided in this invention is better thana traditional CBOW model and a skip-gram model in performance.

Description

technical field [0001] The invention relates to a method for extracting a coal mine safety accident ontology concept, in particular to a method for extracting a coal mine safety accident ontology concept based on a word vector and a conditional random field. Background technique [0002] Coal safety production is a comprehensive system engineering, which involves the interaction and linkage of the four elements of personnel, equipment, environment, and management. It needs to integrate many links and information such as coal mining, excavation, electromechanical, ventilation, ground survey, and water control. As a form of knowledge base, ontology can effectively describe concepts and the relationship between concepts, has sharing and reusability, and supports logical reasoning. Aiming at the characteristics of data in the field of coal mine safety accidents, construct a coal mine safety accident ontology with reasoning ability and semantic consistency, and form the interconn...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06F16/953G06F17/27G06Q50/02G06Q50/26
CPCG06Q50/02G06Q50/265G06F40/211G06F40/284G06F40/30
Inventor 刘秀磊刘思含刘旭红李红臣崔展奇
Owner BEIJING INFORMATION SCI & TECH UNIV
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