Large quantity of text classification based on the improved feature-line method

Authors:
XianFei Zhang;BiCheng Li;WenBin Mu;Yin Liu
Affiliations:
Zhengzhou Information Science and Technology Institute, Zhengzhou, Henan, China;Zhengzhou Information Science and Technology Institute, Zhengzhou, Henan, China;Zhengzhou Information Science and Technology Institute, Zhengzhou, Henan, China;Zhengzhou Information Science and Technology Institute, Zhengzhou, Henan, China
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

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Abstract

Feature-Line Method deems that a line between two points in the same class of space represents the space feature better than a single point. However, it brings faults in the classification results in terms of distance only. Here coefficient was put forward to eliminate the influence of the off-group point to classification, which was also combined with the central distance of class, then formed the improved algorithm,which is used in two different capacity document repositories. The results of experiment show that the improved algorithm support large document repositories very well, and it can be used in large-scale text classification and text retrieval.