|| D. Sullivan, Document Warehousing and Text Mining, Wiley Computer Publishing, 2001, pp. 326.|
 G.. Salton and M. J. McGill, Introduction to Modern Retrieval, McGraw-Hill Book Company, 1983.
 J. Dorre, P. Gerstl and R. Seiffert, Text Mining: Finding Nuggets in Mountains of Textual Data, Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1999, pp. 398-401.
 J. Han, M. Amber, Data Mining: Concept and Techniques , Morgan Kaufmann, 2000.
 P. Willet, Recent Trens in Hierarchical Document Clustering: A Critical Review, Information Processing and Management, 24(5), 1988, pp. 557-597.
 R. Sebastiani, Machine Learning in Automated Text Categorization. ACM Computing Surveys, Vol. 34, No.1, March 2002, pp. 1-47.
 Y. Yang and J. O. Pedersen, A comparative study on feature selection in text categorization. In Proceedings of 14th International Conference on Machine Learning, Morgan Kaufmann, 1997, pp. 412-420.
 L. D. Baker and A. McCallum, Distributional clustering of words for text classification. In SIGIR’98: Proceedings of the 21st Annual International ACM SIGIR, pp. 96–103. ACM, August 1998.
 N. Slom and Tishby, The power of word clusters for text classification. In Proceedings of 23rd European Colloquium on Information Research (ECIR), 2001.
 R. Bekkerman, R. El-Yaniv, Y. Winter, and N. Tishby, On feature distributional clustering for text categorization. In ACM SIGIR, pp. 146–153, 2001.
 F. Pereira, N. Tishby and L. Lee, Distributional clustering of English words. In 31st Annual Meeting of ACL, 1993, pp. 183-190.
 S. Deerwester, S. T. Dumais, G. W. Furnas, T. K. Landauer, and R. Harshman, Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science, Vol. 41, NO. 6, 1990, pp. 391-407.
 I. S. Dhillon, S. Mallela and R. Kumar, A Divisive Infromation-Theoretic Feature Clustering Algorithm for Text Classification. Journal of Machine Learning Research 3, 2003, pp. 1265-1287.
 A Mc Callum, K. Nigam and L. Ungar, Efficient Clustering of High-dimensional Data Sets with Application to Reference Matching. In Proceedings of the 6th International Conference on Knowledge Discovery and Data Mining, 2000, pp. 169-178.