alexa Abstract | Study on personal preferences mining method in O2O E-commerce model

Journal of Chemical and Pharmaceutical Research
Open Access

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Abstract

In this paper, we studied the theory of personalized recommendation, compared the different recommendation technologies, and analyzed the applicability of several recommendation technologies to the O2O mode of e-commerce. And then an approach for mining personal context-aware preferences from the context-rich device logs, or context logs for short, and exploit these identified preferences for building personalized context-aware recommender systems was proposed. The experiment results show that the recommendation method put forward in the thesis is able to meet the demand of the O2O e-commerce mode.

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Author(s): Shang Peini and Yuan Feiyun

Keywords

O2O E-commerce, Personal preferences, Data Mining, user data

 
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