Database Marketing |
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Understanding Consumer Database Marketing Denise D. Schoenbachler, Geoffrey L. Gordon, Dawn Foley and Linda Spelman Journal of Consumer Marketing, V14, No. 1, 1997 |
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Alternative Approaches to Cluster-based Market Segmentation Paul E. Green, Abba M. Kreiger Journal of the Market Research Society |
Feature Selection, Stepwise Regression |
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Introduction to the Logistic Regression Model
Ch.1 From "Applied Logistic Regression" by Hosmer and Lemeshow, Wiley, 1989. |
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The Problem of Underestimating the Residual Error Variance in forward Stepwise Regression Pages 1 2 3 4 5 6 7 8 L.S. Freedman, D. Pee, D. N. Midthune The Statistician 41(4), 1992, pp 405-412 |
Clustering & Segmentation |
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CACTUS-Clustering Categorical Data Using Summaries Venkatesh Ganti, Raghu Ramakrishnan, Johannes Gehrke DEMON project Proc. 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-99), 1999 Aug, pp. 73-83 |
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Chameleon: Hierarchical Clustering Using Dynamic Modeling George Karypis, Eui-Hong (Sam) Han, Vipin Kumar IEEE Computer, 32(8), 1999 Aug, pp. 68-75 |
Combining Multiple Models |
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Combining Predictors Leo Breiman in COMBINING ARTIFICIAL NEURAL NETS: Ensemble and Modular Multi-Net Systems Edited: Amanda Sharkey Publisher: Springer-Verlag London Ltd 1999 |
Beyond Association Rules |
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Mining the Most Interesting Rules Roberto J. Bayardo Jr., Rakesh Agrawal See 1999 ACM SIGMOD Workshop on Research Issues in DMKD Proc. 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-99), 1999 Aug, pp. 145-154 |
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Constraint-Based Rule Mining in Large, Dense Databases
Roberto J. Bayardo Jr., Rakesh Agrawal and Dimitrios Gunopulos Proceedings of the 15th International Conference on Data Engineering, 1999 Mar, Sydney, Austrialia, IEEE CS Press, 1999 Scheines, R. |
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Beyond Market Baskets: Generalizing Association Rules to Correlations(Dependence Rules) Craig Silverstein, Sergey Brin, Rajeev Motwani Data Mining and Knowledge Discovery, 2, 1998, pp. 39-68 |
Support Vector Machines |
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Support vector classifiers: a first look David M.J. Tax, D. de Ridder, Robert P.W. Duin Proceedings of the Third Annual Conference of the Advanced School for Computing and Imaging, ASCI, Delft, June 1997 |
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On Support Vector Decision Trees for Database Marketing Kristin P. Bennett, D. H. Wu, L. Auslender .P.I Math Report No. 98-100, Rensselaer Polytechnic Institute, Troy, NY, 1998 |
Web Mining & Information Retrieval |
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A Framework for Collaborative, Content-Based and Demographic Filtering Michael J. Pazzani Artificial Intelligence (in press) |
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Mining the Web's Link Structure Soumen Chakrabarti, Byron E. Dom, S. Ravi Kumar, Prabhakar Raghavan, Sridhar Rajagopalan, Andrew Tomkins, David Gibson, and Jon Kleinberg IEEE Computer, 32(8), Aug, 1999, pp. 60-67 |
Sampling |
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Is Sampling Useful in Data Mining? A Case in the Maintenance of Discovered Association Rules S.D. Lee, David W. Cheung, Ben Kao Data Mining and Knowledge Discovery, An International Journal, Vol. 2, pp. 233-262, Kluwer Academic Publishers, 1998 |
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Sampling: Design and Analysis
Sharon Lohr Duxbury Press, 1999, pp 272-280 |
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Sampling Large Databases for Association Rules Hannu Toivonen In 22th International Conference on Very Large Databases (VLDB'96), 134-145, Mumbay, India, September 1996. Morgan Kaufmann |
Scalability Issues |
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Mining Very Large Databases Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishnan IEEE Computer, 32(8), Aug, 1999, pp. 38-45 |
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The Effects of Training Set Size on Decision Tree Complexity Tim Oates, David Jensen Proceedings of the 14th International Conference on Machine Learning. 1997 |
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An Exploratory Technique for Investigating Large Quantities of Categorical Data G. Kass Applied Statistics, 29, 1980 |
Miscellaneous |
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MetaCost: A General Method for Making Classifiers Cost-Sensitive
Pedro Domingos Proc. 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-99), 1999 Aug, pp. 155-164 |