A Novel Three-Dimensional Recommendation Approach for C2C E-Commerce Platform

Abstract:

The recommendation problem in C2C e-commerce platform is three-dimensional, for it involves three entities: buyers, products and sellers. Traditional two-dimensional recommendation methods used in B2C websites are not applicable for the new task of recommending seller and product combinations to the target buyer in C2C websites. We formally defined the recommendation problem in C2C, and proposed a three-dimensional approach by compounding and extending collaborative filtering and content-based filtering method. In the proposed approach, buyer similarity and seller similarity are measured to model the buyers personalized preferences, and a rating inference mechanism is employed to reduce the data sparsity caused by multi-dimensions. The model and the key calculations of the approach are discussed. And an example of calculation is demonstrated.

• Periodical: Advanced Materials Research (Volume 717)
• Pages: 714-719
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.717.714
• Online since: July 2013
• Authors: Dan Xiang Ai, Hui Zuo, Jun Yang
• Keywords: C2C, E-Commerce Recommendation, Three-Dimensional Recommendation

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