Combining trust and reputation as user influence in cross domain group recommender system (CDGRS)
Author:
Affiliation:
1. Department of Computer Engineering, UVPCE, Ganpat University, Gujarat, India
2. Department of Computer Science, University of Delhi, India
Publisher
IOS Press
Subject
Artificial Intelligence,General Engineering,Statistics and Probability
Reference32 articles.
1. Ricci F. , Rokach L. , Shapira B. and Kantor P. , Recommender Systems Handbook. New York, USA: Springer, 2011.
2. Das Abhinandan S. , Datar Mayur , Ashutosh Garg and Rajaram Shyam , Google news personalization: scalable online collaborative filtering,” in Proceedings of the 16th international conference on World Wide Web, Banff, Alberta, Canada, 2007, pp. 271–280.
3. Bedi P. , Agarwal S.K. , Jindal V. and Richa , MARST: Multi-Agent Recommender System for e-Tourism Using Reputation Based Collaborative Filtering,” in International Workshop on Databases in Networked Information Systems, Aizu-Wakamatsu City, Japan, 2014, 189–201.
4. Hybrid recommender system: survey and experiments,”;Burke;User Modeling and User-Adapted Interaction Journal,2002
5. Badrul Sarwar , Karypis George , Konstan Joseph and Riedl John , Item-Based Collaborative Filtering Recommendation Algorithms,” in Proceedings of the 10th international conference on World Wide Web, Hong Kong, 2001, pp. 285–295.
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