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
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;
Conference_Titel :
Information Acquisition, 2004. Proceedings. International Conference on
Print_ISBN :
0-7803-8629-9
DOI :
10.1109/ICIA.2004.1373386
