Problem Description Study how to adaptively aggregate recommender systems on a per-user and per-item basis when combining results from complementing prediction methods. Create a flexible algorithm that combines multiple - Personalization - Document - PDFSEARCH.IO

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	Problem Description Study how to adaptively aggregate recommender systems on a per-user and per-item basis when combining results from complementing prediction methods. Create a flexible algorithm that combines multiple Add to Reading List Document Date: 2014-01-21 18:26:56 Open Document File Size: 1,82 MB Share Result on Facebook City Trondheim / / Company Implementation 81 B Resources / Recommender Systems / / / Facility Information Science Norwegian University of Science / Norwegian University of Science / / IndustryTerm personalized search scenario / personalized search / aggregation algorithm / / Organization Computer and Information Science Norwegian University of Science and Technology Trondheim / Department of Computer and Information Science / Department of Computer / Norwegian University of Science and Technology / / Person Asbjørn Thomassen / Kim Joar Bekkelund / Kjetil Valle / / Position Supervisor / supervisor / assistant professor / / Technology artificial intelligence / resulting aggregation algorithm / Information Technology / / SocialTag Human–computer interaction Personalization Science Collective intelligence Information science Information retrieval Recommender system

Problem Description Study how to adaptively aggregate recommender systems on a per-user and per-item basis when combining results from complementing prediction methods. Create a flexible algorithm that combines multiple Add to Reading List