Title: Multi-criteria fuzzy approach to recommendation system based on a social trust model

Authors: Pardeep Kumar; Ajeet Kumar

Addresses: Department of Computer Science, Sindh Madressatul Islam University, Karachi, Pakistan ' Sindh Textbook Board, Jamshoro, Sindh, Pakistan

Abstract: In recent years, recommender systems have been researched in the extreme due to information overload caused by the increasing number of e-commerce sites. A recommender system aims to provide users with personalised online product or service recommendations to handle the increasing online information overload problem and improve customer relationship management. In general, users provide overall rating to items but recently rating on multiple characteristics of the items have been studied and is in the developing phase. So much research work has been made in the past to build a recommendation system focusing on the ratings of a single criterion. However, no work has been done which takes into account multi-criteria with user social trust score. This paper presents a novel recommendation system approach using social trust score and fuzzy-based metaheuristic approach. This hybrid recommendation method can improve the prediction quality of recommendation system.

Keywords: web recommendation; recommendation system; fuzzy linguistic; fuzzy multi-criteria; decision making.

DOI: 10.1504/IJCI.2021.122709

International Journal of Collaborative Intelligence, 2021 Vol.2 No.3, pp.224 - 230

Received: 27 May 2021
Accepted: 09 Jul 2021
Published online: 06 May 2022 *

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