Multi‐Criteria Decision‐Making Recommender System Based on Users’ Reviews
Sahbi Sidhom, Amira Kaddour · 2022
This chapter aims to improve the recommendation task by using text mining techniques in order to capture the multi-criteria of users' interests from the users' reviews. It considers two algorithms, namely the primary criterion-based recommendation system and the multi-criteria text mining-based recommendation system. The chapter is devoted to the multi-criteria decision-making methods. It then describes the basic concepts of recommender systems and related works. Next, the chapter details the proposed solution, considering improvement versions that were tested on a real database extracted from the TripAdvisor website. The experimental study shows that the proposed solution provides motivating results compared with the existing works. Future research consists of exploiting the ontology to describe the multi-criteria content and their relationships. The latter can be used to analyze in depth the users’ reviews and to increase the performance of recommendation systems.