Title
Modelling trust networks using resistive circuits for trust-aware recommender systems
Abstract
AbstractRecommender systems have been widely used for predicting unknown ratings. Collaborative filtering as a recommendation technique uses known ratings for predicting user preferences in the item selection. However, current collaborative filtering methods cannot distinguish malicious users from unknown users. Also, they have serious drawbacks in generating ratings for cold-start users. Trust networks among recommender systems have been proved beneficial to improve the quality and number of predictions. This paper proposes an improved trust-aware recommender system that uses resistive circuits for trust inference. This method uses trust information to produce personalized recommendations. The result of evaluating the proposed method on Epinions dataset shows that this method can significantly improve the accuracy of recommender systems while not reducing the coverage of recommender systems.
Year
DOI
Venue
2017
10.1177/0165551516628733
Periodicals
Keywords
Field
DocType
Collaborative filtering,recommender systems,resistive circuits,trust-aware recommender system
Recommender system,Data mining,Collaborative filtering,Information retrieval,Inference,Computer science,Resistive circuits
Journal
Volume
Issue
ISSN
43
1
0165-5515
Citations 
PageRank 
References 
3
0.39
11
Authors
3
Name
Order
Citations
PageRank
Mehdi Hosseinzadeh Aghdam12059.88
Morteza Analoui212424.94
Peyman Kabiri313211.94