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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Reasoning-based Intelligent Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
