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