Text/Reference Books, Materials, and Sites

1. "C4.5: program for machine learning". by Ross Quinlan, Morgan Kaufman, 1993.
2. "An introduction to support vector machines". by Nello Cristianini and John Shawe-Taylor, Cambridge University Press 2000.
3. "Data Mining" by P. Adriaans and Dolf Zantinge
4. "Predictive Data Mining: A practical Guide" by S.M. Weiss, N. Indurkhya
5. "Data Mining: Tools and Review" by C. Hall
6. "Data Mining Techniques: for Marketing, Sales, and Customer Support" by M. Berry
7. Fast Algorithms for Mining Association Rules, by R. Agrawal, R. Srikant, VLDB-94.
8. Parallel Mining of Association Rules, by R. Agrawal, J.C. Shafer: IEEE Transactions on Knowledge and Data Engineering, Vul. 8, No. 6, December 1996.
9. Mining Sequential Patterns, by R. Agrawal and R. Srikant, "Proc. of the Int'l Conference on Data Engineering (ICDE), Taipei, Taiwan, March 1995. "Fast Algorithms for Mining Association Rules", by R. Agrawal, R. Srikant, Proc. of the 20th Int'l Conference on Very Large Databases, Santiago, Chile, Sept. 1994. PDF format.
10. "BIRCH: An Efficient Data Clustering Method for Very Large Databases", by T. Zhang, R. Ramakrishnan, and M. Livny, SIGMOD96, 103-114.
11. Mining Frequent Patterns without Candidate Generation (PDF), by J. Han, J. Pei, and Y. Yin, Proc. 2000 ACM-SIGMOD Int. Conf. on Management of Data (SIGMOD'00), Dallas, TX, May 2000.
12. "Integrating Classification and Association Rule Mining." by Bing Liu, Wynne Hsu, Yiming Ma, Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), New York, USA, 1998. [PostScript Paper]
13. ''Discovery of Multiple-Level Association Rules from Large Databases'', by J Han and Y. Fu. Proc. of 1995 Int'l Conf. on Very Large Data Bases (VLDB'95).
14. "Pruning and Summarizing the Discovered Associations", by Bing Liu, Wynne Hsu, Yiming Ma, Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD-99), August 15-18, 1999, San Diego, CA, USA. [Postscript]
15. Supervised and unsupervised discretization of continuous features, by James Dougherty, Ron Kohavi, and Mehran Sahami. ML-95.
16. "Feature Selection for Classification". Intelligent Data Analysis - An International Journal, Elsevier, Vol. 1, No. 3, pages 131 - 156, 1997.
17. Data Clustering: A Review , by A K Jain, M N Murty, ACM Computing Surveys, 1999.
18. "Efficiently Mining Long Patterns from Databases", by R. J. Bayardo Jr., Proc. of the ACM SIGMOD Conference on Management of Data, Seattle, Washington, 85-93, June 1998. PDF format.
19. "RAINFOREST - A Framework for Fast Decision Tree Construction of Large Datasets". by J. E. Gehrke, Raghu Ramakrishnan, and Venkatesh Ganti. In Proceedings of the Twenty-fourth International Conference on Very Large Data Bases, New York, New York, 1998. paper
20. "The Anatomy of a Large-Scale Hypertextual Web Search Engine", by Brin-Page, WWW7 / Computer Networks 30(1-7): 107-117 (1998) htm
21. A re-examination of text categorization methods. by Yiming Yang and Xin Liu, Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'99, pp 42--49), 1999.
22. K. Nigam, A. McCallum, S. Thrun, & T. Mitchell. Text classification from labeled and unlabeled documents using EM", by K. Nigam, A. McCallum, S. Thrun, & T. Mitchell, Machine learning journal, 2000.
23. "Partially Supervised Classification of Text Documents." by Bing Liu, Wee Sun Lee, Philip S Yu and Xiaoli Li. Proceedings of the Nineteenth International Conference on Machine Learning (ICML-2002), 8-12, July 2002, Sydney, Australia. [PostScript] [PDF]
24. Searching the Workplace Web, by Ronald Fagin, Ravi Kumar, Kevin S. McCurley, Jasmine Novak, D.Sivakumar, John Tomlin, David P. Williamson

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