DocumentCode
2206551
Title
Intelligence text categorization based on Bayes algorithm
Author
Yu, Fei ; An, Yiyao ; Li, Hong ; Zhu, Miaoliang ; Yang, Ouyang
Author_Institution
Sch. of Comput. & Commun., Hunan Univ., Changsha, China
fYear
2004
fDate
21-25 June 2004
Firstpage
347
Lastpage
350
Abstract
Text categorization is the basic technology of information process, query and retrieval. This paper introduces some improvements of the Bayes categorization algorithm based on an advanced research on current algorithm. In addition, it considers the probable risk of mistaking the related text for unrelated one during the text categorization and puts forward a proposal of a text categorization model of minimal-risk Bayes decision. The results of our experiments prove that it promotes the precision of text categorization.
Keywords
Bayes methods; information retrieval; learning (artificial intelligence); text analysis; Bayes categorization algorithm; information process; information query; information retrieval; intelligence text categorization; minimal-risk Bayes decision; Algorithm design and analysis; Artificial intelligence; Eigenvalues and eigenfunctions; Frequency; History; Information processing; Information retrieval; Internet; Testing; Text categorization;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Acquisition, 2004. Proceedings. International Conference on
Print_ISBN
0-7803-8629-9
Type
conf
DOI
10.1109/ICIA.2004.1373386
Filename
1373386
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