Text-oriented method for extracting cognitive relationships among knowledge topics

A relation extraction and text technology, applied in text database query, unstructured text data retrieval, special data processing applications, etc., can solve problems such as slow construction process, and achieve the effect of helping learning

Active Publication Date: 2019-08-30
XI AN JIAOTONG UNIV
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

At present, high-quality cognitive relationships between knowledge topics require domain experts to label according to domain knowledge, and the construction process is slow

Method used

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  • Text-oriented method for extracting cognitive relationships among knowledge topics
  • Text-oriented method for extracting cognitive relationships among knowledge topics
  • Text-oriented method for extracting cognitive relationships among knowledge topics

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Embodiment Construction

[0051] The present invention will be further described in detail below in conjunction with specific embodiments, which are explanations of the present invention rather than limitations.

[0052] Taking Wikipedia as the knowledge source as an example, the Wikipedia entries are extracted to form a knowledge thesaurus, and the extracted entries correspond to the text abstracts of Wikipedia pages to form the text to be recognized. The data acquisition and processing process of Wikipedia is as follows: figure 2 shown. Extracted Wikipedia entries such as image 3 As shown, the content of the abstract of the extracted Wikipedia text is as follows Figure 4 shown.

[0053] The present invention specifically comprises the following steps, see figure 1 :

[0054] (1) Preprocessing the text to be recognized to obtain the preprocessing result text, such as Figure 6 As shown, it mainly includes 5 steps:

[0055] (1.1) Extract the domain terms in the text to be recognized to form a k...

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Abstract

The invention provides a text-oriented method for extracting cognitive relationships among knowledge topics, which not only judges the dependency relationships among the knowledge topics, but also hasdirectivity. Learning of knowledge themes can be guided according to the filtered cognitive relationship triple. The method comprises the following steps: (1) preprocessing a to-be-identified text toobtain a preprocessing result text; (2) extracting word features and sentence features influencing the cognitive relationship in the preprocessing result text in combination with the words and sentence layer factors to form a cognitive relationship feature set; (3) utilizing a multi-node marking rule to mark a sentence level sequence through the trained conditional random field model; according to the cognitive relationship feature set, extracting all cognitive relationship triplets in the sentence; and (4) calculating the importance of knowledge subject words in the cognitive relationship triplet, and filtering the extracted cognitive relationship triplet according to a word importance principle so as to extract the cognitive relationship among the knowledge subjects.

Description

technical field [0001] The invention relates to a method for cognitive relations among knowledge subjects, in particular to a text-oriented method for extracting cognitive relations among knowledge subjects. Background technique [0002] The rapid development of information technology and the popularization of the Internet have brought massive digital resources. The huge digital resources have caused great difficulties for learners to quickly, orderly and accurately obtain the required knowledge, and it is easy to cause problems such as learning lost. Therefore, how to alleviate this problem has become one of the urgent problems in the information field. Its core is how to realize the Internet information with huge data and lack of information, according to the internal connection between knowledge topics, that is, the cognitive relationship between knowledge topics, and organize knowledge topics together in an orderly manner. Taking knowledge topics as the main research ob...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27G06F16/335G06F16/33
CPCG06F16/335G06F16/3344G06F40/242G06F40/216G06F40/295G06F40/30
Inventor 刘均麻珂欣曾宏伟任若清
Owner XI AN JIAOTONG UNIV
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