Data Mining: The Textbook



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IEEE Transactions on Knowledge and Data Engineering, 19(3), pp. 355–369, 2007.



  1. S. Forrest, C. Warrender, and B. Pearlmutter. Detecting intrusions using system calls: alternate data models. IEEE ISRSP, 1999.




  1. S. Fortunato. Community Detection in Graphs. Physics Reports, 486(3–5), pp. 75–174, February 2010.




  1. A. Frank, and A. Asuncion. UCI Machine Learning Repository, Irvine, CA: University of California, School of Information and Computer Science, 2010. http://archive.ics.uci.edu/ml

BIBLIOGRAPHY

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  1. J. Friedman, R. Kohavi, and Y. Yun. Lazy decision trees. Proceedings of the National Conference on Artificial Intelligence, pp. 717–724, 1996.




  1. B. Fung, K. Wang, R. Chen, and P. S. Yu. Privacy-preserving data publishing: A survey of recent developments. ACM Computing Surveys (CSUR), 42(4), 2010.




  1. G. Gan, C. Ma, and J. Wu. Data clustering: theory, algorithms, and applications. SIAM, 2007.




  1. V. Ganti, J. Gehrke, and R. Ramakrishnan. CACTUS: Clustering categorical data using summaries. ACM KDD Conference, pp. 73–83, 1999.




  1. M. Garey, and D. S. Johnson. Computers and intractability: A guide to the theory of NP-completeness. New York, Freeman, 1979.




  1. H. Galhardas, D. Florescu, D. Shasha, and E. Simon. AJAX: an extensible data cleaning tool. ACM SIGMOD Conference 29(2), pp. 590, 2000.




  1. J. Gao, and P.-N. Tan. Converting output scores from outlier detection algorithms into probability estimates. ICDM Conference, pp. 212–221, 2006.




  1. M. Garofalakis, R. Rastogi, and K. Shim. SPIRIT: Sequential pattern mining with regular expression constraints. VLDB Conference, pp. 7–10, 1999.




  1. T. Gartner, P. Flach, and S. Wrobel. On graph kernels: Hardness results and efficient

alternatives. COLT: Kernel 2003 Workshop Proceedings, pp. 129–143, 2003.





  1. Y. Ge, H. Xiong, Z.-H. Zhou, H. Ozdemir, J. Yu, and K. Lee. Top-Eye: Top-k evolving trajectory outlier detection. CIKM Conference, pp. 1733–1736, 2010.




  1. J. Gehrke, V. Ganti, R. Ramakrishnan, and W.-Y. Loh. BOAT: Optimistic decision tree construction. ACM SIGMOD Conference, pp. 169–180, 1999.




  1. J. Gehrke, R. Ramakrishnan, and V. Ganti. Rainforest-a framework for fast decision tree construction of large datasets. VLDB Conference, pp. 416–427, 1998.




  1. D. Gibson, J. Kleinberg, and P. Raghavan. Clustering categorical data: an approach based on dynamical systems. The VLDB Journal, 8(3), pp. 222–236, 2000.




  1. M. Girvan, and M. Newman. Community structure in social and biological networks.




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