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Comprehensive Review Reading List

Database/ Data Mining

  1. Michael Stonebraker Joseph M. Hellerstein:”What Goes Around Comes Around” Readings in Database Systems, Fourth Edition Morgan Kaufmann 2005.
  2. Heinrichs, J. H. and J. Lim (2003). "Integrating Web-Based Data Mining Tools With Business Models For Knowledge Management." Decision Support Systems 35(1): 103-112.
  3. Fabrizio Sebastiani. “Machine learning in automated text categorization. ACM Comput. Surv. 34(1): 1-47 (2002).
  4. Li, X-B. “A scalable decision tree system and its application in pattern recognition and intrusion detection”, Decision Support Systems 41 (2005) 112-130.
  5. Chen, M.-S., Han, J. and Yu, P. S. “Data Mining: An Overview from a Database Perspective,” IEEE Transactions on Knowledge and Data Engineering, 8(6):866-883, 1996.
  6. Gengm L. and Hamilton, H. J. "Interestingness Measures for Data Mining: A Survey", ACM Computing Surveys, 38(2), 2006.
  7. Hand, D. “Statistics and Data Mining: Intersecting Disciplines”, in SIGKDD Explorations, page 16-19, 1999, also found in http://www.son.wisc.edu/rdsu/library/hand.pdf.
  8. V. Verykios and E. Bertino and I. Fovino and L. Provenza and Y. Saygin and Y. Theodoridis. “State-of-the-art in privacy preserving data mining,” SIGMOD Record 33 (2004) 50--57", 2004, available online at http://citeseer.csail.mit.edu/713858.html.
  9. Thuraisingham, B. “Privacy -Preserving Data Mining: Developments and Directions”, Journal of Database Management: Jan-Mar 2005, 16, 1: 75-87.
  10. Clifton, C., Kantarcioglu, M., and Vaidya, J. “Defining Privacy for Data Mining”, in National Science Foundation Workshop on Next Generation Data Mining, pages 126-133, 2002. Available online at http://cimic.rutgers.edu/~jsvaidya/pub-papers/ngdm-privacy.pdf.
  11. Mukherjee, S., Chen, Z. and Gangopadhyay, A. “A Privacy Preserving Technique for Euclidean Distance-Based Mining Algorithms Using Fourier-Related Transforms”, The VLDB Journal, 15:293-315, 2006.
  12. L. Sweeney, k-anonymity: a model for protecting privacy. International Journal on Uncertainty, Fuzziness and Knowledge-based Systems, 10 (5), 2002; 557-570
  13. Jim Gray, Surajit Chaudhuri, Adam Bosworth, Andrew Layman, Don Reichart, Murali Venkatrao, Frank Pellow, Hamid Pirahesh, Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals, Data Mining and Knowledge Discovery, Volume 1, Issue 1, Mar 1997, Pages 29 - 53.
  14. S. Chaudhuri and U. Dayal. An Overview of Data Warehousing and OLAP Technology. ACM SIGMOD Record, 26(1):65--74, March 1997.
  15. Sarawagi, S., Agrawal, R., and Megiddo, N. “Discovery-driven Exploration of OLAP Data Cubes, in proceedings of EDBT'98, pages 168-182, 1998.
  16. Wu, M.-C. and Buchmann, A. "Research Issues in Data Warehousing", in Datenbanksysteme in Buro, Technik und Wissenschaft, pp. 61-82, 1997.
  17. Jing, J. and Helal, S. and Elmagarmid, A. “Client Server Computing in Mobile Environments”, ACM Computing Surveys, Vol. 31, No. 2, June 1999.
  18. D. Zhang, G. Karabatis, Z. Chen, B. Adipat, L. Dai, Z. Zhang “Personalization and Visualization on Handheld Devices”, ACM Symposium on Applied Computing, Dijon, France, April 2006.
  19. A. Halevy, A. Rajaraman, J. Ordille. "Data Integration: The Teenage Years". Proceedings of the 32nd International Conference on Very Large Data Bases (VLDB), September 2006, Seoul, Korea, pp. 9-16.
  20. S. Chawathe, H. Garcia-Molina, J. Hammer, K. Ireland, Y. Papakonstantinou, J. Ullman, and J. Widom. "The TSIMMIS Project: Integration of Heterogeneous Information Sources". In Proceedings of IPSJ Conference, pp. 7-18, Tokyo, Japan, October 1994.
  21. G. Karabatis. "Using Context in Semantic Data Integration", Journal of Interoperability in Business Information Systems, Volume 1, Number 3, December 2006, pp. 9-21
  22. Z. Chen, A. Gangopadhyay, G. Karabatis, M. McGuire, C. Welty. “Semantic Integration and Knowledge Discovery for Environmental Research”, Journal of Database Management, IDEA Group, Hershey, PA, Volume 18, Number 1, January-March 2007, pp. 43-68
  23. Martin Ester, Hans-Peter Kriegel, Jörg Sander (University of Munich), Algorithms and Applications for Spatial Data Mining, Published in Geographic Data Mining and Knowledge Discovery, Research Monographs in GIS, Taylor and Francis, 2001. http://www.dbs.informatik.uni-muenchen.de/Publikationen/Papers/Chapter7.revised.pdf
  24. K. Koperski, J. Adhikary, and J. Han. Spatial data mining: Progress and challenges survey paper, 1996. http://citeseer.ist.psu.edu/cache/papers/cs/45/ftp:zSzzSzftp.fas.sfu.
    cazSzpubzSzcszSzhanzSzkddzSzsdm96.pdf/koperski96spatial.pdf
  25. S. Shekhar, C.T. Lu, P. Zhang Detecting Graph-based Spatial Outliers: Algorithms and Applications, Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2001, San Francisco, CA, 2001. An extended version appeared in International Journal of Intelligent Data Analysis, 6(5), IOS press.
  26. V. P. Janeja and V. Atluri, "FS3: A Random Walk based Free-Form Spatial Scan Statistic for Anomalous Window Detection". The Fifth IEEE International Conference on Data Mining (ICDM), November 2005, Houston, TX.
  27. N. R. Adam, V. P. Janeja, V. Atluri, Neighborhood Based Detection of Anomalies in High Dimensional Spatio-temporal Sensor Datasets, ACM Symposium on Applied Computing (ACM SAC), March 2004, Cyprus.
  28. Brewer, E. “Combining Systems and Databases: A Search Engine Retrospective,” in Readings in Database Systems, Fourth Edition Morgan Kaufmann, pp. 711-724, 2005.
  29. Brin, S. and Page, L. “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” in Readings in Database Systems, Fourth Edition Morgan Kaufmann, pp. 725-744, 2005.
  30. D. Chamberlin, R. Astrahan et al. “A History and Evaluation of System R”, CACM Vol. 24, No. 10, October 1981.