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

• Success of e-commerce depends greatly on an effective product recommender design.
• The social recommender system can accurately generate personalized products.
• Recommendation sources include the factors of preference, trust, and relationships.
• The proposed framework can effectively promote retailer's products and services.

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.