SIGKDD 2002 - PDF Preprint Papers

SIGKDD 2002

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SIGKDD
2002

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The True Lift Model - A Novel Data Mining Approach to Response Modeling in Database Marketing

14 years 7 days ago

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In database marketing, data mining has been used extensively to find the optimal customer targets so as to maximize return on investment. In particular, using marketing campaign d...

Victor S. Y. Lo

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Id	Views	Title	Status

1	232	The True Lift Model - A Novel Data Mining Approach to Response Modeling in Database Marketing	claim
2	172	Data Mining, National Security, Privacy and Civil Liberties	claim
3	162	Background and Overview for KDD Cup 2002 Task 1: Information Extraction from Biomedical Articles	claim
4	136	A Survey on Wavelet Applications in Data Mining	claim
5	129	Multi-Relational Data Mining: a Workshop Report	claim
6	117	Classification trees for problems with monotonicity constraints	claim
7	113	Combining Data and Text Mining Techniques for Yeast Gene Regulation Prediction: A Case Study	claim
8	94	BIOKDD01: Workshop on Data Mining in Bioinformatics	claim
9	93	Randomization in Privacy-Preserving Data Mining	claim
10	93	A Perspective on Inductive Databases	claim
11	92	A Machine Learning Approach for the Curation of Biomedical Literature - KDD Cup 2002 (Task 1)	claim
12	90	Database Privacy	claim
13	90	Cryptographic Techniques for Privacy-Preserving Data Mining	claim
14	86	Report on the SIGKDD-2002 Panel The Perfect Data Mining Tool: Interactive or Automated	claim
15	83	Towards Effective and Interpretable Data Mining by Visual Interaction	claim
16	81	P-tree Classification of Yeast Gene Deletion Data	claim
17	78	Report on the SIGKDD 2001 Conference Panel "New Research Directions in KDD"	claim
18	78	Predicting the Effects of Gene Deletion	claim
19	74	MobiMine: Monitoring the Stock Market from a PDA	claim
20	73	Discovery in multi-attribute data with user-defined constraints	claim
21	71	Applying Data Mining to Intrusion Detection: The Quest for Automation, Efficiency, and Credibility	claim
22	69	The Genomics of a Signaling Pathway: A KDD Cup Challenge Task	claim
23	69	Why so many clustering algorithms: a position paper	claim
24	66	Feature Engineering for a Gene Regulation Prediction Task	claim
25	66	Learning missing values from summary constraints	claim
26	66	Exploiting succinct constraints using FP-trees	claim
27	64	The Inference Problem: A Survey	claim
28	62	KDD Cup 2001 Report	claim
29	61	One Class SVM for Yeast Regulation Prediction	claim
30	54	Mining Data Streams under Block Evolution	claim
31	53	SPARTAN: using constrained models for guaranteed-error semantic compression	claim

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