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

研究成果: Article同行評審

151 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)740-752
頁數13
期刊Decision Support Systems
55
發行號3
DOIs
出版狀態Published - 1 六月 2013

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