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This paper investigates trust-based recommendation systems in social networks, emphasizing the importance of item ratings and trust graph structures for effective recommendations. It introduces a Weighted Average framework for constructing recommendation systems and addresses challenges like cold-start users and adversarial attacks. The authors propose a first principles approach to develop and evaluate various recommendation algorithms based on different types of information, including trust graphs, intra-

Author

Karan Pathania

Language

EN