Recommendation based on object typicality

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

doi:10.1145/1871437.1871664

Recommendation based on object typicality

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

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-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 language	English
Title of host publication	CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops
Pages	1529-1532
Number of pages	4
DOIs	https://doi.org/10.1145/1871437.1871664
Publication status	Published - 1 Dec 2010
Externally published	Yes
Event	19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 - Toronto, ON, Canada Duration: 26 Oct 2010 → 30 Oct 2010

Publication series

Name	International Conference on Information and Knowledge Management, Proceedings

Conference

Conference	19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
Country	Canada
City	Toronto, ON
Period	26/10/10 → 30/10/10

Keywords

Object typicality
Recommendation system

ASJC Scopus subject areas

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

More information

10.1145/1871437.1871664

Cite this

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title = "Recommendation based on object typicality",

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.",

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author = "Yi Car and Leung, {Ho Fung} and Qing Li and Jie Tang and Juanzi Li",

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Car, Y, Leung, HF, Li, Q, Tang, J & Li, J 2010, Recommendation based on object typicality. in CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops. International Conference on Information and Knowledge Management, Proceedings, pp. 1529-1532, 19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10, Toronto, ON, Canada, 26/10/10. https://doi.org/10.1145/1871437.1871664

Recommendation based on object typicality. / Car, Yi; Leung, Ho Fung; Li, Qing; Tang, Jie; Li, Juanzi.

CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops. 2010. p. 1529-1532 (International Conference on Information and Knowledge Management, Proceedings).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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