Personalised ranking online reviews based on user individual preferences
by Wei Song; Shiwei Zhang; Lizhen Liu; Hanshi Wang
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 10, No. 1, 2018

Abstract: With the development of e-commerce sites, online reviews have become important data resources for e-customers. Nowadays, there have been many literatures on the category of reviews category or ranking for public. However, they only satisfy common preferences, and ignore personalised preferences of individual users. In view of this phenomenon, this paper is trying to put forward a ranking method for individual preferences. It begins with collecting the rules of user preferences by showing reviews to them to let them mark the reviews they like. Then it combines the common rules with user personalised rules to get the range of features. Finally, after calculating the optimal solution of features, the paper strives to structure a ranking model to rank reviews with the set of optimal solution.

Online publication date: Wed, 11-Apr-2018

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