Incorporating multi-criteria ratings in recommendation systems

Hsin Hsien Lee, Wei-Guang Teng

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

36 Citations (Scopus)

Abstract

Recommendation systems utilize information techniques to the problem of helping users find the items they would like. Example applications include the recommendation systems for movies, books, CDs and many others. As recommendation systems emerge as an independent research area, the rating structure plays a critical role in recent studies. Among many alternatives, the collaborative filtering algorithms are generally accepted to be successful to estimate user ratings of unseen items and then to derive proper recommendations. In this paper, we extend the concept of single criterion ratings to multi-criteria ones, i.e., an item can be evaluated in many different aspects. Since there are usually conflicts among different criteria, the recommendation problem cannot be formulated as an optimization problem any more. Instead, we propose to use data query techniques to solve this multi-criteria recommendation problem.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Information Reuse and Integration, IEEE IRI-2007
Pages273-278
Number of pages6
DOIs
Publication statusPublished - 2007 Dec 1
Event2007 IEEE International Conference on Information Reuse and Integration, IEEE IRI-2007 - Las Vegas, NV, United States
Duration: 2007 Aug 132007 Aug 15

Publication series

Name2007 IEEE International Conference on Information Reuse and Integration, IEEE IRI-2007

Other

Other2007 IEEE International Conference on Information Reuse and Integration, IEEE IRI-2007
CountryUnited States
CityLas Vegas, NV
Period07-08-1307-08-15

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Information Systems and Management
  • Electrical and Electronic Engineering

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