收稿日期: 2004-08-09
修回日期: 2004-11-08
网络出版日期: 2005-09-15
A Fast Text Categorization Approach Based on k-Nearest Neighbor
Received date: 2004-08-09
Revised date: 2004-11-08
Online published: 2005-09-15
张庆国 , 张宏伟 , 张君玉 . 一种基于k最近邻的快速文本分类方法[J]. 中国科学院大学学报, 2005 , 22(5) : 554 -559 . DOI: 10.7523/j.issn.2095-6134.2005.5.004
k-Nearest Neighbor (k-NN) is one of the simplest and most effective algorithms for text categorizat ion. However, k-NN search requires intensive similarity computations, part icularly for large training set, the search of the whole set is unacceptable. Therefore, speeding-up k-NN search is a key for making k-NN categorizat ion useful in practice. In this paper a fast text categorization approach based on k-NN, which can classify textual documents quickly and efficiently on condition of searching in the very large training set is presented. Experiment shows that the new algorithm can greatly improve the performance.
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