Abstract—The Collaborative Recommender Systems provide personalized recommendations to users using the rating profiles of different users. These systems should maintain accurate model of user’s interests and needs by collecting the user preferences either explicitly or implicitly using numerical scale. Although most of the current systems maintain single user ratings in the user-item ratings matrix, these single ratings do not provide useful information regarding the reason behind the user’s preference. However, the multicriteria based systems provide an opportunity to compute accurate recommendations by maintaining the details of user preferences in multiple aspects. Apart from this, the user ratings are usually subjective, imprecise and vague in nature, because it is based on user’s perceptions and opinions. Fuzzy sets seem to be an appropriate paradigm to handle the uncertainty and fuzziness of human decision making behavior and to effectively model the natural complexity of human behavior. Because of these reasons, this paper adopts the Fuzzy linguistic approach to efficiently represent the user ratings and the Fuzzy Multicriteria Decision Making (FMCDM) approach to accurately rank the relevant items to a user. This work empirically evaluates the proposed approach’s performance through a Music Recommender system developed for this research. The proposed approach’s performance is compared to traditional user-based and item-based recommendation algorithms. From the evaluation results, it is observed that the proposed approach shows improvement in recommendations than the traditional algorithms.
Index Terms—Collaborative filtering, E-commerce, Fuzzy linguistic, Fuzzy multicriteria decision making, Recommender systems.
K. Palanivel (* corresponding author) is with the AVC College, Mayiladuthurai, Bharathidasan University, Tamil Nadu, INDIA. (Ph: 91-9443501690; e-mail: firstname.lastname@example.org).
R. Sivakumar is with AVVM Sri Pushpam College, Thanjavur, Bharathidasan University, Tamil Nadu, INDIA. (Ph: 9443662536; e-mail: email@example.com).
Cite: K. Palanivel and R. Sivakumar, "Fuzzy Multicriteria Decision-Making Approach for Collaborative Recommender Systems," International Journal of Computer Theory and Engineering vol. 2, no. 1, pp. 57-63, 2010.