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Chinese text term extracting method utilizing quadratic mutual information

A technology of mutual information and terminology, applied in special data processing applications, natural language data processing, instruments, etc., can solve the problem of low accuracy rate of single feature term extraction, achieve strong field adaptability, low noise of extraction results, and high accuracy rate high effect

Active Publication Date: 2017-02-22
BEIJING INSTITUTE OF TECHNOLOGYGY
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Problems solved by technology

[0021] The present invention proposes a Chinese text term extraction method using secondary mutual information, which solves the problem of low accuracy of term extraction using a single feature term in the term extraction task, by combining three statistical features of secondary mutual information, word frequency, and word length The part-of-speech features and the removal of redundant terms based on the nesting relationship between terms improve the accuracy of term extraction

Method used

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  • Chinese text term extracting method utilizing quadratic mutual information
  • Chinese text term extracting method utilizing quadratic mutual information
  • Chinese text term extracting method utilizing quadratic mutual information

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Embodiment Construction

[0061] In order to better illustrate the purpose and advantages of the present invention, the implementation of the method of the present invention will be further described in detail below in conjunction with examples.

[0062] The data source used in the experiment is the book "Water Supply Water Quality Testing 3: Water Quality Analysis Technology", which was published by Water Conservancy and Hydropower Press on October 1, 2014. It consists of four chapters and 18 subsections. During the experiment, terms were extracted from the text content of each chapter and section of the book, and the statistical information of the data source is shown in Table 1.

[0063] Table 1. Data source of term extraction experiment

[0064]

[0065] Among them, the effective number of words refers to the number of remaining words after removing characters other than hyphens and Chinese characters.

[0066] The experimental procedure is as follows:

[0067] Step 1, import the experimental ...

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Abstract

The invention relates to a Chinese text term extracting method utilizing quadratic mutual information and belongs to a computer science and natural language processing technology. The method comprises the steps that firstly, core words are expanded into multiple candidate terms by combining the quadratic mutual information, word frequency, word length and word characteristics based on previous and later core word expansion, then redundant terms centralized in a candidate set are removed and the terms are graded and sorted according to the nest relation of the terms, the word length and the word frequency characteristics. The method comprehensively considers the language rules and statistical characteristics of the terms, and the term extraction accuracy is improved.

Description

technical field [0001] The invention relates to a Chinese text term extraction method using secondary mutual information, and belongs to the technical field of computer science and natural language processing. Background technique [0002] Term extraction is the process of extracting phrases from the text that can describe the subject of the text and have completeness and domain representation. Term extraction is an important basic research task in the field of natural language processing technology, and has important applications in many fields such as automatic summarization, information retrieval, text classification and clustering. [0003] Terminology is a collection of titles used to represent concepts in a specific field, also known as professional terms or technical terms. The characteristics of terms are usually summarized into two measurable features: 1) Unithood, which measures whether a term can express an independent and complete meaning and has a stable struct...

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Application Information

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IPC IPC(8): G06F17/27
CPCG06F40/284
Inventor 罗森林陈倩柔潘丽敏吴舟婷
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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