Building a Robust Decentralized Recommender System for Web Credibility Evaluation
نویسنده
چکیده
The size and diversity of today’s online content makes it hard for the users to evaluate its credibility. To address this problem, we aim to build a fully-decentralized and robust recommender system to support web credibility assessment. In this proposal, we highlight three pieces of work that serve as starting points for our research, which we organize in a number of steps: (1) an extensive analysis of the factors involved in user credibility assessment, (2) designing a distributed recommender system that handles data sparsity and misrepresentation, and (3) devising incentives for users to cooperate and contribute to the system with ratings. In addition, we aim to employ a decentralized architecture that leaves users in control of their data.
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