1Yang Y, Liu X. A re-examination of text categorization methods. In: Proceedings of 22nd Annual International ACMSIGIR Conference on Research and Development in Information Retrieval ( SIGIR'99 ) . Berkeley: ACM Press, 1999. 42 ~ 49
2He J,Tan AH, Tan CL. A comparative study on Chinese text categorization methods. In: Proceedings of the International Workshop on Text and Web Mining. Singapore: Melbourne,2000. 24~ 35
3Cover TM, Hart PE. Nearest neighbor pattern classification. IEEE Transactions on Information Theory, 1968, IT-13: 21 ~ 27
4Hart PE. Condensed nearest neighbor rule. IEEE Transactions on Information Theory, 1968, IT-14:515 ~ 516
5Li RL, Hu YF. Noise reduction to text categorization based on density for k NN. In: Proceeding of the Second International Conference on Machine Learning and Cybernetics. Xi'an,2003. 3119~ 3124
6Hwang WJ, Wen KW. Fast k NN classification algorithm based on partial distance search. Electronics Letters, 1998,34(21 ) :2006 ~ 2063
7Baek SJ, Sung KM. Fast K-nearest-neighbour search algorithm for nonparametric classification. Electronics Letters ,2000,36(21 ) :1821 ~ 1822
8Grabowski S. Voting over multiple k-NN classifier. TCSET'2002. 2002. 223 ~ 225
9Denoeux T. A k-nearest neighbor classification rule based on dempster-shafer theory. IEEE Trans on Systems, Man, and Cybernetics, 1995,25 (5):804 ~ 813
10Zhang B, Srihari SN. A fast algorithm finding k-nearest neighbors with non-metric dissimilarity. In: Proceedings of the Eighth International Workshop on Frontiers in Handwriting Recognition( IWFHR' 02). 2002