DocumentCode :
3181010
Title :
Research on Text Classification Algorithm of Largest Dispersion Based on Term Frequency
Author :
Junxiu, An ; Yuchang, Jin
Author_Institution :
Sch. of Software Eng., Chengdu Univ. of Inf. Technol. (CUIT), Chengdu, China
Volume :
1
fYear :
2009
fDate :
25-27 Dec. 2009
Firstpage :
400
Lastpage :
403
Abstract :
In order to achieve a document in accordance with the contents of the page automatic classification, put forward the largest dispersion of text classification algorithm based on the term frequency. The algorithm using backward term frequency algorithm for the n-types typical texts confirm the scientific and effective characteristics set of n-types; rely on it, getting the classification values of Webpage documents in the n-types characteristics set through adopt to the largest dispersion algorithm, getting the largest dispersion after dispersion comparison; and then compared the largest dispersion value with relative threshold, if the value is larger than the threshold, it is the type of webpage documents, but if the value is smaller than the threshold, the judgement about the type of document is invalid. The algorithm has good robustness and easy-to-use, which is very effective for the large-scale data of small documents.
Keywords :
Internet; pattern classification; text analysis; Web page document; backward term frequency algorithm; largest dispersion algorithm; n-types characteristics set; page automatic classification; text classification algorithm; Artificial intelligence; Classification algorithms; Dispersion; Frequency; Large-scale systems; Robustness; Software algorithms; Testing; Text categorization; Vocabulary; retrospect term frequency algorithm; text classification algorithm; the characteristics set; the largest dispersion algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
Conference_Location :
Chongqing
Print_ISBN :
978-0-7695-3930-0
Electronic_ISBN :
978-1-4244-5423-5
Type :
conf
DOI :
10.1109/IFCSTA.2009.103
Filename :
5385048
Link To Document :
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