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A Robust Collaborative Recommendation Algorithm Incorporating Trustworthy Neighborhood Model
2014
Journal of Computers
The conventional collaborative recommendation algorithms are quite vulnerable to user profile injection attacks. To solve this problem, in this paper we propose a robust collaborative recommendation algorithm incorporating trustworthy neighborhood model. Firstly, we present a method to calculate the users' degree of suspicion based on the user-item ratings data using the theory of entropy and the idea of density-based local outlier factor. Based on it, we measure the user's trust attributes
doi:10.4304/jcp.9.10.2328-2334
fatcat:zo3tsg2gvzcsxfhnanodflfbmy