Titlebook: E-Commerce, and Web Technologies; 14th International C Christian Huemer,Pasquale Lops Conference proceedings 2013 Springer-Verlag Berlin He

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Edward W. Gondolf,Ellen R. Fishers show that it is possible to manipulate binary rating-based recommender systems’ predictions by inserting malicious user profiles. Hence, it is shown that na?ve Bayesian classifier-based collaborative filtering scheme is not robust against shilling attacks.

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Friedrich Porz,Andreas Podeswik performance of our system by analysing the time and memory requirements as the number of agents increases, and by looking whether the behaviours of agents have any significant effect on the system’s overall performance.

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https://doi.org/10.1007/978-3-319-72071-5ns evoked by items in the movie and music domains, and results from an offline evaluation that show accuracy improvements on model-based recommender systems that incorporate the extracted item emotional information.