A social recommender mechanism for e-commerce: Combining similarity, trust, and relationship

Yung-Ming Li*, Chun Te Wu, Cheng Yang Lai

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

149 Scopus citations

Abstract

Online business transactions and the success of e-commerce depend greatly on the effective design of a product recommender mechanism. This study proposes a social recommender system that can generate personalized product recommendations based on preference similarity, recommendation trust, and social relations. Compared with traditional collaborative filtering approaches, the advantage of the proposed mechanism is its comprehensive consideration of recommendation sources. Accordingly, our experimental results show that the proposed model outperforms other benchmark methodologies in terms of recommendation accuracy. The proposed framework can also be effectively applied to e-commerce retailers to promote their products and services.

Original languageEnglish
Pages (from-to)740-752
Number of pages13
JournalDecision Support Systems
Volume55
Issue number3
DOIs
StatePublished - 1 Jun 2013

Keywords

  • Analytic hierarchy process
  • E-commerce
  • Preference similarity
  • Social recommender systems
  • Social relation
  • Trust

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