Toward affective recommendation: A contextual association approach for eliciting user preference

Xiaohui Li, Tomohiro Murata

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

1 Citation (Scopus)

Abstract

The explosive growth of recommender systems has resulted in realization of individualized service as commercial patterns and research prototypes. However, the traditional recommendation approaches are overemphasized the similarity between user preference and items feature. They are completely ignored affectivity that was a crucial factor. Our study focuses on exploring a new affective recommendation approach of semantic associated extension by integrating the Spreading Activation model with knowledge of cognitive psychology for the real-time preference-aware. This paper presents an affectivity-based recommendation approach to eliciting a characteristic sequence consisted of color nodes mapping the relationships between user preference with his mood and items feature. Predominance of our proposal was illustrated through an instantiation of movie recommender system that was developed based on the proposed approach. The testing results of performance show that our affectivity-based recommendation approach outperformed the traditional collaborative filtering approach in terms of the accuracy. This paper also presents a novel insight into exploitation of rich repository of domain-specific knowledge to provide real-time recommendation for user.

Original languageEnglish
Title of host publicationInternational Conference on Information Society, i-Society 2011
Pages47-54
Number of pages8
Publication statusPublished - 2011
EventInternational Conference on Information Society, i-Society 2011 - London
Duration: 2011 Jun 272011 Jun 29

Other

OtherInternational Conference on Information Society, i-Society 2011
CityLondon
Period11/6/2711/6/29

    Fingerprint

Keywords

  • Cognitive psychology
  • Color detection
  • Recommender system
  • Spreading activation
  • WordNet

ASJC Scopus subject areas

  • Information Systems
  • Social Sciences (miscellaneous)

Cite this

Li, X., & Murata, T. (2011). Toward affective recommendation: A contextual association approach for eliciting user preference. In International Conference on Information Society, i-Society 2011 (pp. 47-54). [5978506]