|Table of Contents|

Research of Text Subject Extraction Based on Improved Weight for Bayesian Reasoning and TFIDF Algorithm(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2014年01期
Page:
57-
Research Field:
计算机科学
Publishing date:

Info

Title:
Research of Text Subject Extraction Based on Improved Weight for Bayesian Reasoning and TFIDF Algorithm
Author(s):
Shao Xiaogen1; Ju Xunguang1; Hu Juxin1; Ma Zhongwei2
(1.Department of Information and Electrical Engineering,Xuzhou Institute of Technology,Xuzhou 221111,China) (2.College of Information Engineering,Xiangtan University,Xiangtan 411105,China)
Keywords:
Bayesian reasoning; position weight; topic words extraction; TFIDF algorithm
PACS:
TP391; TP301
DOI:
-
Abstract:
The shortcoming of the TFIDF algorithm is improved for Chinese text topic word extraction.This paper considers the keywords appearing frequency,position weight in the text,the hybrid algorithm of Bayesian Reasoning and TFIDF was designed to extracte topic words,and the topic words was extracted from forward,reverse and middle based on sorting position of the candidate words.The results was higher average accuracy than the simple TFIDF by 6.2%.

References:

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Last Update: 2014-03-30