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논문검색

Collaborative filtering recommender system based on approximate constraint satisfaction

초록

영어

As the rapid growth of mobile device, a recommender system is required to provide adequate recommendation list even if the customers provide their needs explicitly. In this research, the problem that customers provide their needs is modeled as constraint satisfaction problem. However the existing constraint satisfaction is too rigid, so we employ approximate constraint satisfaction by adopting indifference interval. The proposed recommendation methodology is composed of two phases; the first phase is related to CF-based filtering to generate the candidate
recommendation set. The second phase is related to approximate constraint filtering to find the final adequate items fitting individual customers’ concerns. We expect that the proposed methodology contribute to display the adequate items to customer’s concerns for better recommendation in mobile environment.

목차

Abstract
 1. Introduction
 2. Related work
  2.1 Collaborative filtering system
  2.2 Approximate constraint satisfaction problem
 3. Methodology
  3.1 Overall view
  3.2 Phase 1: CF-based filtering
  3.3 Phase 2: Constraint-based filtering
 4. An illustrative example
  4.1 Phase 1: CF-based filtering
 5. Conclusion and future work
 Reference

저자정보

  • Il Young Choi School of Business Administration, Kyunghee University
  • Hyea Kyeong Kim School of Business Administration, Kyunghee University
  • Jae Kyeong Kim School of Business Administration, Kyunghee University
  • Young U. Ryu School of Management, University of Texas at Dallas

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