Creative Marketing as Application of Chance Discovery

[1]  Haym Hirsh,et al.  Learning to Predict Rare Events in Event Sequences , 1998, KDD.

[2]  G. N. Lance,et al.  A General Theory of Classificatory Sorting Strategies: 1. Hierarchical Systems , 1967, Comput. J..

[3]  M.V. Joshi,et al.  On evaluating performance of classifiers for rare classes , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

[4]  Steve Benford,et al.  Ambiguity as a resource for design , 2003, CHI '03.

[5]  Yukio Ohsawa,et al.  Modeling the Process of Chance Discovery , 2003, Chance Discovery.

[6]  Nick Roussopoulos,et al.  Nearest neighbor queries , 1995, SIGMOD '95.

[7]  Yukio Ohsawa,et al.  KeyGraph: Visualized Structure Among Event Clusters , 2003, Chance Discovery.

[8]  Peter McBurney,et al.  Chance Discovery , 2003, Advanced Information Processing.

[9]  Vipin Kumar,et al.  Predicting Rare Classes: Comparing Two-Phase Rule Induction to Cost-Sensitive Boosting , 2002, PKDD.

[10]  Ramakrishnan Srikant,et al.  Fast algorithms for mining association rules , 1998, VLDB 1998.

[11]  Y. Ohsawa,et al.  Chance Discovery By Stimulated Groups Of People. Application To Understanding Consumption Of Rare Food , 2002 .

[12]  M. Greenacre.  Correspondence analysis in practice , 1993 .

[13]  Vipin Kumar,et al.  Predicting rare classes: can boosting make any weak learner strong? , 2002, KDD.

[14]  Naoaki Okazaki,et al.  Polaris: An Integrated Data Miner for Chance Discovery , 2003 .

[15]  Jiawei Han,et al.  Data Mining: Concepts and Techniques , 2000 .