R. Agrawal, R. Srikant: "Fast Algorithms for Mining Association Rules", Proc. of the 20th Int'l Conference on Very Large Databases, Santiago, Chile,Sept. 1994. Expanded version available as IBM Research Report RJ9839, June 1994. |
Hannu Toivonen: "Sampling large databases for association rules" In 22th International Conference on Very Large Databases (VLDB'96),134 - 145, Mumbay, India, September 1996. Morgan Kaufmann. |
R. Srikant, Q. Vu, R. Agrawal: "Mining Association Rules with Item Constraints", Proc. of the 3rd Int'l Conference on Knowledge Discovery in Databases and Data Mining, Newport Beach, California, August 1997. |
Mannila, Toivonen:"Multiple uses of frequent sets and condensed representations",KDD 1996. |
R. Srikant, R. Agrawal: "Mining Quantitative Association Rules in Large Relational Tables", Proc. of the ACM-SIGMOD 1996 Conference on Management of Data, Montreal, Canada, June 1996. |
Yonatan Aumann, Yehuda Lindell: "A Statistical Theory for Quantitative Association Rules". 261-270, Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 15-18, 1999, San Diego, CA, USA. ACM, 1999 |
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan: "Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications", Proc. of the ACM SIGMOD Int'l Conference on Management of Data, Seattle, Washington, June 1998. |
Luc Dehaspe and Hannu Toivonen:"Frequent query discovery: a unifying ILP approach to association rule mining", Report CW-258, Department of Computer Science, Katholieke Universiteit Leuven, Belgium, March 1998. |
Wei-Yin Loh, Y.-S. Shih: Split selection methods for classification trees. Statistica Sinica, 1997, vol. 7, pp. 815-840. Lim, T.-S., Loh, W.-Y., and Shih, Y.-S. (2000), A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms, Machine Learning Journal, vol. 40, pp. 203-228. QUEST Hompage |
Haixun Wang, Carlo Zaniolo: CMP: A Fast Decision Tree Classifier Using Multivariate Predictions,. ICDE 2000: 449-460 |
Ankerst M., Elsen C., Ester M., Kriegel H.-P.: Visual Classification: An Interactive Approach to Decision Tree Construction, Proc. 5th Int. Conf. on Knowledge Discovery and Data Mining (KDD'99), San Diego, CA, 1999, pp. 392-396. PS-Version Ankerst M., Ester M., Kriegel H.-P.: Towards an Effective Cooperation of the Computer and the User for Classification, Proc. ACM SIGKDD Int. Conf. on Knowledge Discovery & Data Mining (KDD'2000), Boston, MA, 2000. |
Ankerst M., Breunig M. M., Kriegel H.-P., Sander J.: OPTICS: Ordering Points To Identify the Clustering Structure, Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD'99), Philadelphia, PA, 1999, pp. 49-60. Ester M., Kriegel H.-P., Sander J., Xu X.: A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise, Proc. 2nd Int. Conf.on Knowledge Discovery and Data Mining (KDD'96), Portland, OR, 1996, pp. 226-231. |
Breunig S., Kriegel H.-P., Ng R., Sander J.: LOF: Identifying Density-Based Local Outliers, Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD 2000), Dallas, TX, 2000. Clustering Home-Page München |
Sridhar Ramaswamy, Rajeev Rastogi, Kyuseok Shim: Efficient Algorithms for Mining Outliers from Large Data Sets. SIGMOD Conference 2000: 427-438 |
David Gibson, Jon M. Kleinberg, Prabhakar Raghavan: Clustering Categorical Data: An Approach Based on Dynamical Systems. VLDB 1998: 311-322 |
Sudipto Guha, Rajeev Rastogi, Kyuseok Shim: ROCK: A Robust Clustering Algorithm for Categorical Attributes. ICDE 1999: 512-521 |
Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishnan: CACTUS - Clustering Categorical Data Using Summaries. KDD 1999: 73-83 |
Charu C. Aggarwal, Cecilia Magdalena Procopiuc, Joel L. Wolf, Philip S. Yu, Jong Soo Park: Fast Algorithms for Projected Clustering. SIGMOD Conference
1999: 61-72 Charu C. Aggarwal, Philip S. Yu: Finding Generalized Projected Clusters In High Dimensional Spaces. SIGMOD Conference 2000: 70-81 |