Research on text-reducing method based on the improved KNN algorithm

Authors:
Peiyu Liu;Ye Qiu;Lina Zhao
Affiliations:
School of Information Science and Engineering, Shandong Normal University, Jinan, China;School of Information Science and Engineering, Shandong Normal University, Jinan, China;School of Information Science and Engineering, Shandong Normal University, Jinan, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 4
Year:
2009

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Abstract

There are relevance and redundancy of the fearure 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.