Paper for Presentation

Association Mining

  1. (Present by: Rencan Yan) Jiawei Han, Jian Pei, Yiwen Yin, Mining Frequent Patterns without Candidate Generation, SIGMOD 2000
  2. (Present by: Vinod Kumar Putchala) Ke wang, Yu He, and Jiawei Han, Mining Frequent Itermsets Using Support Constraints, VLDB 2000.
  3. (Present by: Srikanth Dola) Mohammed J. Zaki, Generating non-redundant association rules, KDD 2000
  4. (Present by: Ying Yang) Bing Liu, Minqing Hu and Wynne Hsu, Multi-level organization and summarization of the discovered rules, KDD 2000.
  5. (Present by: ) H. Lu, L. Feng, and J. Han, `` Beyond Intra-Transaction Association Analysis: Mining Multi-Dimensional Inter-Transaction Association Rules '', ACM Transactions on Information Systems, 18(4): 423-454, 2000

Classification

  1. (Present by: ) Dimitris Meretakis and Beat Wüthrich, Extending naïve Bayes classifiers using long itemsets, KDD 1999
  2. (Present by: Srinivas Rao Gona) Hongjun Lu and Hongyan Liu,  Decision Tables: Scalable Classification Exploring RDBMS Capabilities, VLDB 2000
  3. (Present by: Dien Trang Luu) Glenn Fung and O. L. Mangasarian,  Multicategory Proximal Support Vector Machine Classifiers , KDD 2001
  4. (Present by: Tom Sillence) Andreas Buja and Yung-Seop Lee,  Data Mining Criteria for Tree-Based Regression and Classification , KDD 2001
  5. (Present by: ) Volker Tresp, The Generalized Bayesian Committee Machine , KDD 2000
  6. (Present by: ) Glenn Fung and O. L. Mangasarian, Data selection for support vector machine classifiers , KDD 2001
  7. (Present by: ) Johannes Gehrke, Raghu Ramakrishnan, and Venkatesh Ganti, RainForest--A Framework for Fast Decision Tree Construction over Large Datasets, VLDB 1998
  8. (Present by: ) K. Alsabti, S. Ranka and V. Singh, CLOUDS: A Decision Tree Classifer for Large Datasets, KDD 1998

Clustering

  1. (Present by: Igor Grinshpan) S. Guha, R. Rastogi, and K. Shim, CURE: An Efficient Clustering Algorithm for Large Databases, SIGMOD 1998
  2. (Present by: Mayumi Kato) Andrew McCallum, Kamal Nigam and Lyle H. Ungar, Efficient clustering of high-dimensional data sets with application to reference matching, KDD 2000
  3. (Present by: ) A. K. H. Tung, J. Han, L. V. S. Lakshmanan, and R. T. Ng, `` Constraint-Based Clustering in Large Databases '', Proc. 2001 Int. Conf. on Database Theory (ICDT'01), London, U.K., Jan. 2001.
  4. (Present by: Naveen Kumar Reddy Kolani) Karypis, G., Han, E.-H., and Kumar, V. (1999). Chameleon: Hierarchical Clustering Using Dynamic Modeling. IEEE Computer, Vol. 32(8):pp. 68--75.

Web Mining

  1. (Present by: Steve O'Hara) Gary William Flake, Steve Lawrence and C. Lee Giles, Efficient identification of Web communities, KDD 2000
  2. (Present by: Xianghui Yin) Neel Sundaresan and Jeonghee Yi, Mining the Web for Relations, WWW9 2000

Data Mining Applications

  1. (Present by: Qi Shu) Yanlei Diao, Hongjun Lu, Songting Chen, Zengping Tian, Toward Learning Based Web Query Processing, VLDB 2000
  2.  (Present by: Bodepudi AjithKumar) F. Bonchi, F. Giannotti, G. Mainetto and D. Pedreschi, A classification-based methodology for planning audit strategies in fraud detection, KDD 1999
  3. (Present by: ) G. Dong, J. Han, J. Lam, J. Pei, and K. Wang, `` Mining Multi-Dimensional Constrained Gradients in Data Cubes '', Proc. 2001 Int. Conf. on Very Large Data Bases (VLDB'01), Rome, Italy, Sept. 2001.

Mining Sequence and Trends

  1. (Present by: Raja Gavini) Guozhu Dong and Jinyan Li, Efficient mining of emerging patterns: discovering trends and differences, KDD 1999
  2. (Present by: Chinnappareddy Vara Prasada Reddy) J. Pei, J. Han, H. Pinto, Q. Chen, U. Dayal, and M.-C. Hsu, `` PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth '', Proc. 2001 Int. Conf. on Data Engineering (ICDE'01), Heidelberg, Germany, April 2001.

Multiple Classifier Systems

  1. (Present by: ) Robert E. Schapire and Yoram Singer, BoosTexter: A boosting-based system for text categorization, Machine Learning, 39(2/3):135-168, 2000.
  2. (Present by: ) Yoav Freund, Raj Iyer, Robert E. Schapire and Yoram Singer, An efficient boosting algorithm for combining preferences, Extended abstract appeared in Machine Learning: Proceedings of the Fifteenth International Conference, 1998.

Visulizing Discovered Patterns

  1. (Present by: Lisa Tate) Jianchao Han and Nick Cercone, RuleViz: a model for visualizing knowledge discovery process, KDD 2000, Pages 244 - 253
  2. (Present by: Doug Pollok) Heike Hofmann, Arno P. J. M. Siebes and Adalbert F. X. Wilhelm, Visualizing association rules with interactive mosaic plots, KDD 2000, Pages 227 - 235

Others

  1. (Present by: Ron Lee) Grahne, G.; Lakshmanan, L.V.S.; Xiaohong Wang; Ming Hao Xie, On dual mining: from patterns to circumstances, and back, ICDE 2001, Page(s): 195 -204
  2. (Present by: Chau T. Nguyen) Netz, A.; Chaudhuri, S.; Fayyad, U.; Bernhardt, J., Integrating data mining with SQL databases: OLE DB for data mining , ICDE 2001, Page(s): 379 -387