[1] 程传鹏. 中文网页分类的研究与实现[J]. 中原工学院学报, 2007, 18(1): 61-64. (Cheng Chuanpeng. The Study and Implementation of Chinese Web Page Classification [J]. Journal of Zhongyuan Institute of Technology, 2007, 18(1): 61-64.)
[2] 牛树梓, 程学旗, 郭嘉丰. 排序学习中数据噪音敏感度分析[J]. 中文信息学报, 2012, 26(5): 53-58, 128. (Niu Shuzi, Cheng Xueqi, Guo Jiafeng. Noise Sensitivity in Learning to Rank [J]. Journal of Chinese Information Processing, 2012, 26(5): 53-58, 128.)
[3] Vinciarelli A. Noisy Text Categorization [J]. IEEE Transac­tions on Pattern Analysis and Machine Intelligence, 2005, 27(12): 1882-1895.
[4] 宣照国, 党延忠. 文本分类中粗分类数据噪声修正的网络算法[J]. 情报学报, 2008, 27(5): 670-676. (Xuan Zhaoguo, Dang Yanzhong. Network-based Noise Revision Algorithm in Text Categorization [J]. Journal of the China Society for Scientific and Technical Information, 2008, 27(5): 670-676.)
[5] 王强, 关毅, 王晓龙. 基于特征类别属性分析的文本分类器分类噪声裁剪方法[J]. 自动化学报, 2007, 33(8): 809-816. (Wang Qiang, Guan Yi, Wang Xiaolong. A Method for Eliminating Class Noise in Text Categorization Based on Feature Class Attribute [J]. Acta Automatica Sinica, 2007, 33(8): 809-816.)
[6] 林洋港, 陈恩红.文本分类中基于概率主题模型的噪声处理方法[J].计算机工程与科学, 2010, 32(7): 89-92, 119. (Lin Yanggang, Chen Enhong. A Probabilistic Topic Model Based Noise Processing Method for Text Categorization [J]. Computer Engineering & Science, 2010, 32(7): 89-92, 119. )
[7] Yan J, Liu N, Zhang B, et al. OCFS: Optimal Orthogonal Centroid Feature Selection for Text Categorization [C]. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'05). 2005: 122-129.
[8] Li R L, Hu Y F. Nosice Reduction to Text Categorization Based on Density for KNN [C]. In: Proceedings of the 2nd International Conference on Machine Learning and Cybernetics, Xi'an, China. IEEE, 2003: 3119-3124.
[9] Xu J, Chen C, Xu G, et al. Improving Quality of Training Data for Learning to Rank Using Click-through Data [C]. In: Proceedings of the 3rd ACM International Conference on Web Search and Data Mining. New York: ACM, 2010: 171-180.
[10] Carvalho V R, Elsas J L, Cohen W W, et a1. Suppressing Outliers in Pairwise Preference Rankings[C]. In: Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM'08). New York: ACM, 2008:1487-1488.
[11] Nettleton D F, Orriols-Puig A, Fornells A. A Study of the Effect of Different Types of Noise on the Precision of Supervised Learning Techniques [J]. Artificial Intelligence Review, 2010, 33(4): 275-306.
[12] Tsivtsivadze E, Cseke B, Heskes T. Kernel Principal Component Ranking: Robust Ranking on Noisy Data[C]. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). 2009: 101-113.
[13] Aslam J A, Kanoulas E, Pavlu V, et al. Document Selection Methodologies for Efficient and Effective Learningto-rank [C]. In: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'09). New York: ACM, 2009: 468-475.
[14] Si X, Sun M. Exploring the Concept Levels of Social Tags in Chinese Blogs [C]. In: Proceedings of the 11th Chinese Lexical Semantics Workshop, Suzhou, China. 2010.
[15] 宋玲, 马军, 连莉, 等.文档相似度综合计算研究[J].计算机工程与应用, 2006, 42(30): 160-163. (Song Ling, Ma Jun, Lian Li, et al. The Study on the Comprehensive Computation of the Documents Similarity [J]. Computer Engineering and Applications, 2006,42(30): 160-163.)
[16] 薛晓飞, 张永奎, 任晓东.基于新闻要素的新事件检测方法研究[J]. 计算机应用, 2008, 28(11):2975-2977. (Xue Xiaofei, Zhang Yongkui, Ren Xiaodong.Method Research of New Event Detection Based on News Element [J]. Journal of Computer Applications, 2008, 28(11): 2975-2977.)
[17] 吴慧. 海南省降水量的正态分布特征及正态化变换[J]. 广东气象, 2005, 27(2): 12-13. (Wu Hui.Normal Distribution Characteristics and Variation of Precipitation in Hainan Province [J]. Journal of Guangdong Meteorology, 2005, 27(2): 12-13.)
[18] 王文博. 统计学原理、方法及应用 [M]. 第2版. 西安: 西安交通大学出版社, 2010:94. (Wang Wenbo. Principle, Method and Application of Statistics [M]. The 2nd Edition. Xi'an: Xi'an Jiaotong University Press, 2010: 94.)
[19] Kullback S, Leibler R A. On Information and Sufficiency [J]. Annals of Mathematical Statistics, 1951, 22(1): 79-86.
[20] Vapnik V. The Nature of Statistical Learning Theory[M]. New York: Springer-Verlag, 1999.
[21] Hull D A. Improving Text Retrieval for the Routing Problem Using Latent Semantic Indexing [C]. In: Proceedings of the 17th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.New York: Springer-Verlag, 1994: 282-291.