Recommendation based on object typicality

Yi Car, Ho Fung Leung, Qing Li, Jie Tang, Juanzi Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Current recommendation methods are mainly classified into content-based, collaborative filtering and hybrid methods. These methods are based on similarity measurements among items or users. In this paper, we investigate recommendation systems from a new perspective based on object typicality and propose a novel typicality-based recommendation approach. Experiments show that our method outperforms compared methods on recommendation quality.

Original languageEnglish
Title of host publicationCIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops
Pages1529-1532
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
Event19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 - Toronto, ON, Canada
Duration: 26 Oct 201030 Oct 2010

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
Country/TerritoryCanada
CityToronto, ON
Period26/10/1030/10/10

Keywords

  • Object typicality
  • Recommendation system

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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