An efficient recommender system by integrating non-negative matrix factorization with trust and distrust relationships

Parvin, H, Moradi, P, Esmaeili, S and Jalili, M 2018, 'An efficient recommender system by integrating non-negative matrix factorization with trust and distrust relationships', in Proceedings of the 1st IEEE Data Science Workshop (DSW 2018), Lausanne, Switzerland, 4-6 June 2018, pp. 135-139.


Document type: Conference Paper
Collection: Conference Papers

Title An efficient recommender system by integrating non-negative matrix factorization with trust and distrust relationships
Author(s) Parvin, H
Moradi, P
Esmaeili, S
Jalili, M
Year 2018
Conference name DSW 2018
Conference location Lausanne, Switzerland
Conference dates 4-6 June 2018
Proceedings title Proceedings of the 1st IEEE Data Science Workshop (DSW 2018)
Publisher IEEE
Place of publication United States
Start page 135
End page 139
Total pages 5
Abstract Matrix factorization (MF) has been proved to be an effective approach to build a successful recommender system. However, most current MF-based recommenders cannot obtain high prediction accuracy due to the sparseness of user-item matrix. Moreover, these methods suffer from the scalability issues when applying on large-scale real-world tasks. To tackle these issues, in this paper a social regularization method called TrustRSNMF is proposed that incorporates the social trust information of users in nonnegative matrix factorization framework. The proposed method integrates trust statements along with user-item ratings as an additional information source into the recommendation model to deal with the data sparsity and cold-start issues. In order to evaluate the effectiveness of the proposed method, a number of experiments are performed on two real-world datasets. The obtained results demonstrate significant improvements of the proposed method compared to state-of-the-art recommendation methods.
Subjects Information Systems Management
Pattern Recognition and Data Mining
Dynamical Systems in Applications
Keyword(s) Recommender systems
social Trust
matrix Factorization
distrust Relationships
collaborative filtering
DOI - identifier 10.1109/DSW.2018.8439905
Copyright notice © 2018 IEEE
ISBN 9781538644119
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