Mining preferences from superior and inferior examples

Bin Jiang, Jian Pei, Xuemin Lin, David W. Cheung, Jiawei Han

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Mining user preferences plays a critical role in many important applications such as customer relationship management (CRM), product and service recommendation, and marketing campaigns. In this paper, we identify an interesting and practical problem of mining user preferences: in a multidimensional space where the user preferences on some categorical attributes are unknown, from some superior and inferior examples provided by a user, can we learn about the user's preferences on those categorical attributes? We model the problem systematically and show that mining user preferences from superior and inferior examples is challenging. Although the problem has great potential in practice, to the best of our knowledge, it has not been explored systematically before. As the first attempt to tackle the problem, we propose a greedy method and show that our method is practical using real data sets and synthetic data sets.

Original languageEnglish (US)
Title of host publicationKDD 2008 - Proceedings of the 14th ACMKDD International Conference on Knowledge Discovery and Data Mining
Pages390-398
Number of pages9
DOIs
StatePublished - 2008
Event14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008 - Las Vegas, NV, United States
Duration: Aug 24 2008Aug 27 2008

Publication series

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

Other

Other14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008
Country/TerritoryUnited States
CityLas Vegas, NV
Period8/24/088/27/08

Keywords

  • Inferior examples
  • Preferences
  • Skyline
  • Superior examples

ASJC Scopus subject areas

  • Software
  • Information Systems

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