Mining preferences from superior and inferior examples

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2008, Pages 390-398

  Jiang, Bin ^a   Pei, Jian ^a   Lin, Xuemin ^b   Cheung, David W ^c   Han, Jiawei ^d  

^a SIMON FRASER UNIVERSITY   (Canada)

^b UNIVERSITY OF NEW SOUTH WALES   (Australia)

^c UNIVERSITY OF HONG KONG   (Hong Kong)

^d UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

Inferior examples; Preferences; Skyline; Superior examples

Indexed keywords

CATEGORICAL ATTRIBUTES; CUSTOMER RELATION SHIP MANAGEMENTS; GREEDY METHODS; INFERIOR EXAMPLES; MARKETING CAMPAIGNS; MULTI-DIMENSIONAL SPACES; PRACTICAL PROBLEMS; PREFERENCES; PRODUCT AND SERVICES; REAL DATA SETS; SKYLINE; SUPERIOR EXAMPLES; SYNTHETIC DATA SETS;

INFORMATION MANAGEMENT; MARKETING; PUBLIC RELATIONS;

MINING;

EID: 65449132475     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1401890.1401940     Document Type: Conference Paper

References (20)

1. R. Aggarwal and E. Wimmers. A framework for expressing and combining preferences. In SIGMOD, 2000.
2. S. Borzsonyi, D. Kossmann, and K. Stocker. The skyline operator. In ICDE, 2001.
3. J. Chomicki. Querying with intrinsic preferences. In EDBT, 2002.
4. J. Chomicki. Database querying under changing preferences. Annals of Mathematics and Artificial Intelligence, 2006.
5. R. Duda, P. Hart, and D. Stork. Pattern Classification (2nd edition). John Wiley & Sons, New York, 2001.
6. M. Garey and D. Johnson. Computers and Intractability: a Guide to The Theory of NP- Completeness. Freeman and Company, New York, 1979.
7. S. Holland, M. Ester, and W. Kießling. Preference mining: A novel approach on mining user preferences for personalized applications. In PKDD, 2003.
8. E. Jembere, M. O. Adigun, and S. S. Xulu. Mining context-based user preferences for m-services applications. In WI, 2007.
9. B. Jiang, J. Pei, X. Lin, D. W-L Cheung, and J. Han. Mining preferences from superior and inferior examples. Technical report TR 2008-09, School of Computing Science, Simon Fraser University, 2008.
10. T. Joachims. Optimizing search engines using clickthrough data. In KDD, 2002.
11. S. Y. Jung, J.-H. Hong, and T.-S. Kim. A formal model for user preference. In ICDM, 2002.
12. S. Y. Jung, J.-H. Hong, and T.-S. Kim. A statistical model for user preference. TKDE, 2005.
13. K. Govindarajan and B. Jayaraman and S. Mantha. Preference Queries in Deductive Databases. New Generation Computing, 2001.
14. W. Kießling. Foundations of preferences in database systems. In VLDB, 2002.
15. W. Kießling and G. Kostler. Preference SQL - design, implementation, experience. In VLDB, 2002.
16. H. T. Kung, F. Luccio, and F. P. Preparata. On finding the maxima of a set of vectors. J. ACM, 1975.
17. M. Lacroix and P. Lavency. Preferences; putting more knowledge into queries. In VLDB, 1987.
18. R. D. Lawrence, G. S. Almasi, V. Kotlyar, M. S. Viveros, and S. S. Duri. Personalization of supermarket product recommendations. Data Min. Knowl. Discov., 2001.
19. T. M. Mitchell. Machine Learning. McGraw Hill, 1997.
20. R. E. S. William W. Cohen and Y. Singer. Learning to order things. J. Artif. Intell. Res. (JAIR), 1999.