DocumentCode :
2548293
Title :
Web page categorization based on Maximum Entropy Model
Author :
Lijuan, Jiao ; Liping, Feng
Author_Institution :
Dept. of Comput. Sci., Xinzhou Teachers Univ., Xinzhou, China
fYear :
2010
fDate :
16-18 April 2010
Firstpage :
551
Lastpage :
553
Abstract :
Web page categorization is becoming a pivotal technology in processing and organizing a mass of documents and data. The feature is selected to improve text-processing technology thinking of factor hyperlink in Maximum Entropy Model. Experiment finds that the method is more effective. It not only can get the most consistent distribution, but ensure the accuracy and universality in sorting webpage classification as well. So the webpage-sorting method based on Maximum Entropy Model is a relatively perfect webpage classifying method.
Keywords :
Internet; classification; maximum entropy methods; sorting; text analysis; Web page categorization; Web page sorting method; Webpage classification; Webpage-sorting method; maximum entropy model; pivotal technology; text processing technology; Computer science; Electronic mail; Entropy; Feature extraction; Frequency; Mathematical model; Organizing; Text categorization; Thesauri; Web pages; Maximum Entropy Model; Web page classification; feature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5263-7
Electronic_ISBN :
978-1-4244-5265-1
Type :
conf
DOI :
10.1109/ICIME.2010.5477824
Filename :
5477824
Link To Document :
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