Bekkerman R,El-Yaniv R,Tishby N. Distributional Word Clusters vs Words for Text Categorization. Journal of Machine Learning Research,2003,3: 1183-1208
[2]
Slonim N. The Information Bottleneck: Theory and Application. Ph.D Dissertation. Jerusalem,Israel: The Hebrew University of Jerusalem,2002
[3]
Ye Yangdong,He Xidian,Jia Limin. CD-sIB: A Kind of sIB Algorithm Orient to Categorical Data. Acta Electronica Sinica,2009,37(10): 2165-2172(in Chinese)(叶阳东,何锡点,贾利民.面向范畴类型数据的sIB算法.电子学报,2009,37(10): 2165-2172)
[4]
Seldin Y,Slonim N,Tishby N. Information Bottleneck for Non Co-Occurrence Data // Scholkpf B,Platt J C,Hoffman T,eds. Advances in Neural Information Processing Systems. Cambridge,USA: MIT Press,2007,XIX: 1241-1248
[5]
Shamir O,Sabato S,Tishby N. Learning and Generalization with the Information Bottleneck. Theoretical Computer Science,2010,411(29/30): 2696-2711
[6]
Yuan H Q,Ye Y D. Iterative sIB Algorithm. Pattern Recognition Letters,2011,32(4): 606-614
[7]
Xia Limin,Tan Liqiu,Zhong Hong. Semantic Annotation of Image Based on Information Bottleneck Method. Pattern Recognition and Artificial Intelligence,2008,21(6): 812-818(in Chinese)(夏利民,谭立球,钟 洪.基于信息瓶颈算法的图像语义标注.模式识别与人工智能,2008,21(6): 812-818)
[8]
van Rijsbergen C J. A Theoretical Basis for the Use of Co-occurrence Data in Information Retrieval. Journal of Documentation,1997,33(2): 106-119
[9]
Peat H J,Willett P. The Limitations of Term Co-occurrence Data for Query Expansion in Document Retrieval Systems. Journal of the American Society for Information Science,1991,42(5): 378-383
[10]
Andritsos P,Tsaparas P,Miller R J,et al. LIMBO: Scalable Clustering of Categorical Data // Proc of the 9th International Conference on Extending Database Technology. Heraklion,Greece,2004: 531-532
[11]
Sebastiani F. Machine Learning in Automated Text Categori zation. ACM Computing Surveys,2002,34(1): 1-47
[12]
Cost S,Salzberg S. A Weighted Nearest Neighbor Algorithm for Learning with Symbolic Features. Machine Learning,1973,10(1): 57-78
[13]
Joachims T. A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization // Proc of the 14th International Conference on Machine Learning.San Francisco,USA:Morgan Kaufmann Publishers,1997: 143-151
[14]
Han E H,Karypis G, Kumar V. Text Categorization Using Weight-Adjusted k-Nearest Neighbor Classification // Proc of the Asia Conference on Knowledge Discovery and Data Mining. Hong Kong,China,2001: 53-65
[15]
Shankar S,Karypis G. A Feature Weight Adjustment Algorithm for Document Categorization // Proc of the 6th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York,USA: ACM Press,2000
[16]
Debole F,Sebastiani F. Supervised Term Weighting for Automated Text Categorization // Proc of the ACM Symposium on Applied Computing. Melbourne,USA,2003: 781-788
[17]
Gibson D,Kleinberg J,Raghavan P. Clustering Categorical Data: An Approach Based on Dynamical Systems // Proc of the International Conference on Very Large Data Bases. San Francisco,USA,1998: 311-322
[18]
Yates R B,Neto B R.Modern Information Retrieval. New York,USA: Addison-Wesley-Longman,1999
