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MeSH based medical literature set similarity measurement method

A similarity measurement and medical literature technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve problems such as the inability to mine hidden information similarities, achieve fast and efficient similarity calculations, save human resources, The effect of precise relationship mining

Active Publication Date: 2018-11-23
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In view of the above-mentioned shortcomings in the prior art, the MeSH-based similarity measurement method for medical literature sets provided by the present invention solves the problem that traditional methods only perceive the superficial meaning of documents and cannot mine the similarity of hidden information

Method used

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  • MeSH based medical literature set similarity measurement method
  • MeSH based medical literature set similarity measurement method
  • MeSH based medical literature set similarity measurement method

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Embodiment Construction

[0020] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0021] refer to figure 1 , figure 1 A flow chart showing a MeSH-based similarity measurement method for medical literature collections; as figure 1 As shown, the method 100 includes steps 101 to 106.

[0022] In step 101, search keywords related to diseases or genes are acquired. Taking cancer as an example, there are many types of cancer (BRCA, THCA, UCEC, BLCA...), some are caused by external factors, and some are caus...

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Abstract

The invention discloses a MeSH based medical literature set similarity measurement method, the method comprises the steps of: obtaining a search keyword related to disease or gene; retrieving literatures related to the search keyword, and forming a keyword literature set using all literatures retrieved by same search keyword; mapping the literatures to a vector spatial to construct a MeSH spatialmatrix using a weight value of the medical keyword contained in each literature in the keyword literature set; calculating the weight value of a medical keyword g in the MeSH spatial matrix of a keyword literature set A; constructing a vector formula of the keyword literature set A according to the weight values of the keyword literature set in all medical keywords; and calculating the cosine similarity of the literature set A and a literature set B in the MeSH spatial matrix.

Description

technical field [0001] The invention relates to the calculation of similarity between documents, in particular to a method for measuring the similarity of medical document collections based on MeSH (Vetor Space Model, vector space model). Background technique [0002] The traditional method of calculating the similarity of medical literature collections is to convert the original medical literature data into the relationship between diseases and genes through manual calibration and record them in the database, and establish a genetic association database; The relationship of multiple genes creates a human disease network; and the disease-related gene network is obtained through data indicators such as eigenvector center and betweenness centrality. However, document relationship mining based on manual calibration requires energy to review and cannot meet the speed of new documents; semantic-based document mining involves natural language processing, and the amount of calculat...

Claims

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Application Information

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IPC IPC(8): G06F17/22G06F17/27G06F17/30
CPCG06F40/194G06F40/216
Inventor 邹见效鲁文斌凡时财徐红兵
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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