Trust-aware recommender systems
Proceedings of the 2007 ACM conference on Recommender systems
A model of a trust-based recommendation system on a social network
Autonomous Agents and Multi-Agent Systems
TREPPS: A Trust-based Recommender System for Peer Production Services
Expert Systems with Applications: An International Journal
Improved trust-aware recommender system using small-worldness of trust networks
Knowledge-Based Systems
Applied Intelligence
More reputable recommenders give more accurate recommendations?
Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication
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The trust-aware recommender system (TARS) is a newly proposed trust-aware application. It is able to solve the data sparseness problem of the conventional recommender systems. One of the basic research challenges in TARS is to find the recommenders efficiently. Existing works of TARS use the strategy of random walk to find the recommenders, which is obviously low efficiency. Though the trust network has been verified to be the scale-free network, due to the small power of its degree distributions, we have verified via experiments that the prediction coverage of TARS is very limited by applying the classical routing protocol of scale-free networks directly. We therefore propose a routing protocol for TARS, which is able to efficiently find reliable recommenders for the users of TARS. Our protocol is able to achieve much higher prediction coverage than the classical routing protocol of scale-free networks, while the computational complexity is greatly reduced comparing with existing works of TARS.