Personalised ranking online reviews based on user individual preferences

W Song, S Zhang, L Liu…�- International Journal of�…, 2018 - inderscienceonline.com
W Song, S Zhang, L Liu, H Wang
International Journal of Reasoning-based Intelligent Systems, 2018inderscienceonline.com
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�…
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.
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