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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (9): 28-39    DOI: 10.11925/infotech.2096-3467.2017.09.03
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Building Product Recommendation Model Based on Tags
Tu Haili1(), Tang Xiaobo2
1School of Economics and Management, East China University of Technology, Nanchang 330013, China
2School of Information Management, Wuhan University, Wuhan 430072, China
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[Objective] This paper proposes a personalized product recommendation model based on tags in the social e-commerce environment. [Methods] First, we calculated users’ interests and preferences with the help of tagging frequency and time. Then, we constructed a product ontology of the commercial community based on the tag features and searching conditions of the e-commerce website. Third, we used the ontology to standardize tag semantics, and to classify goods. Fourth, we found clusters containing user preferences, and calculated the similarity between their tags of goods and user preference in the cluster. Finally, we identified the goods which were not tagged but preferred by a specific user. [Results] We examined the model with information of 200 randomly selected active users of popular items from the website of FanDongXi. [Limitations] Only used the frequency and time factor of the users’ tags to calculate their interests and preferences. [Conclusions] The proposed method has better performance than the collaborative filtering recommendation based methods.

Key wordsUser Tag      Product Ontology      User Preference      Recommendation Model     
Received: 07 December 2016      Published: 18 October 2017
ZTFLH:  G35  

Cite this article:

Tu Haili,Tang Xiaobo. Building Product Recommendation Model Based on Tags. Data Analysis and Knowledge Discovery, 2017, 1(9): 28-39.

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