DocumentCode :
2736551
Title :
A Feature Selection Method based on Improved TFIDF
Author :
Yong-qing, WEI ; Pei-yu, LIU ; Zhen-fang, ZHU
Author_Institution :
Shandong Police Coll., Jinan
Volume :
1
fYear :
2008
fDate :
6-8 Oct. 2008
Firstpage :
94
Lastpage :
97
Abstract :
Feature selection is a valid method to reduce the dimension of vector in text categorization system. After analyzed several common evaluation functions for feature selection, we applied terms weight function to feature selection. A new evaluation function based on improved TFIDF method is presented; in this function the category information is introduced to feature items, and the feature items of relevant categories are selected to make up the shortcomings of the TFIDF. Experiments proved that the method is simple and feasible. It´s advantageous in improving the efficiency of the selected feature subset.
Keywords :
feature extraction; text analysis; word processing; TFIDF; evaluation function; feature selection; feature selection method; feature subset; text categorization system; Computational complexity; Educational institutions; Feature extraction; Frequency; IP networks; Large-scale systems; Mutual information; Space technology; Statistics; Text categorization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pervasive Computing and Applications, 2008. ICPCA 2008. Third International Conference on
Conference_Location :
Alexandria
Print_ISBN :
978-1-4244-2020-9
Electronic_ISBN :
978-1-4244-2021-6
Type :
conf
DOI :
10.1109/ICPCA.2008.4783657
Filename :
4783657
Link To Document :
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