1[1]D D Lewis. Naive (Bayes) at forty: The independence assumption in information retrieval. In: The 10th European Conf on Machine Learning(ECML98), New York: Springer-Verlag, 1998. 4～15
2[2]Y Yang, X Lin. A re-examination of text categorization methods. In: The 22nd Annual Int'l ACM SIGIR Conf on Research and Development in Information Retrieval, New York: ACM Press, 1999
3[3]Y Yang, C G Chute. An example-based mapping method for text categorization and retrieval. ACM Trans on Information Systems, 1994, 12(3): 252～277
4[4]E Wiener. A neural network approach to topic spotting. The 4th Annual Symp on Document Analysis and Information Retrieval (SDAIR 95), Las Vegas, NV, 1995
5[5]R E Schapire, Y Singer. Improved boosting algorithms using confidence-rated predications. In: Proc of the 11th Annual Conf on Computational Learning Theory. Madison: ACM Press, 1998. 80～91
6[6]T Joachims. Text categorization with support vector machines: Learning with many relevant features. In: The 10th European Conf on Machine Learning (ECML-98). Berlin: Springer, 1998. 137～142
7[7]S O Belkasim, M Shridhar, M Ahmadi. Pattern classification using an efficient KNNR. Pattern Recognition Letter, 1992, 25(10): 1269～1273
8[8]V E Ruiz. An algorithm for finding nearest neighbors in (approximately) constant average time. Pattern Recognition Letter, 1986, 4(3): 145～147
9[9]P E Hart. The condensed nearest neighbor rule. IEEE Trans on Information Theory, 1968, IT-14(3): 515～516
10[10]D L Wilson. Asymptotic properties of nearest neighbor rules using edited data. IEEE Trans on Systems, Man and Cybernetics, 1972, 2(3): 408～421
