DocumentCode :
2752677
Title :
Research on Text-Reducing Method Based on the Improved KNN Algorithm
Author :
Liu, Peiyu ; Qiu, Ye ; Zhao, Lina
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Normal Univ., Jinan, China
Volume :
4
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
581
Lastpage :
585
Abstract :
There are relevance and redundancy of the feature words in the text vector space, so we proposed a text-reducing method based on the improved KNN algorithm in this paper. Vector polymer theory and feature selection methods were used to reducing the dimension of vector space. Feature words would have more ability to represent categories after feature selection. Experiments proved, the improved KNN algorithm were used in text-reducing not only can reducing the dimension of vector space more effectively, but also can improving the speed and accuracy of the text classify.
Keywords :
feature extraction; pattern classification; text analysis; feature selection methods; feature words; improved KNN algorithm; text classify; text vector space; text-reducing method; vector polymer theory; Fuzzy systems; Independent component analysis; Information science; Internet; Knowledge engineering; Polymers; Principal component analysis; Space technology; Sparse matrices; Statistical analysis; feature selection; similarity degree; text-reducing; vector polymerization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
Type :
conf
DOI :
10.1109/FSKD.2009.616
Filename :
5359247
Link To Document :
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