Min Cao1, Sijing Zhou1, Honghao Gao1,2,3
Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 595-604, 2019, DOI:10.31209/2019.100000114
Abstract Recommender methods using reviews have become an area of active research
in e-commerce systems. The use of auxiliary information in reviews as a way to
effectively accommodate sparse data has been adopted in many fields, such as
the product field. The existing recommendation methods using reviews typically
employ aspect preference; however, the characteristics of product reviews are
not considered adequate. To this end, this paper proposes a novel
recommendation approach based on using product attributes to improve the
efficiency of recommendation, and a hybrid collaborative filtering is presented.
The product attribute model and a new recommendation ranking formula are
introduced… More >
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