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Trust Networks for Recommender Systems (Hardcover, Edition. ed.): Patricia Victor, Chris Cornelis, Martine de Cock Trust Networks for Recommender Systems (Hardcover, Edition. ed.)
Patricia Victor, Chris Cornelis, Martine de Cock
R1,547 Discovery Miles 15 470 Ships in 10 - 15 working days

This book describes research performed in the context of trust/distrust propagation and aggregation, and their use in recommender systems. This is a hot research topic with important implications for various application areas. The main innovative contributions of the work are: -new bilattice-based model for trust and distrust, allowing for ignorance and inconsistency -proposals for various propagation and aggregation operators, including the analysis of mathematical properties -Evaluation of these operators on real data, including a discussion on the data sets and their characteristics. -A novel approach for identifying controversial items in a recommender system -An analysis on the utility of including distrust in recommender systems -Various approaches for trust based recommendations (a.o. base on collaborative filtering), an in depth experimental analysis, and proposal for a hybrid approach -Analysis of various user types in recommender systems to optimize bootstrapping of cold start users.

Trust Networks for Recommender Systems (Paperback, 2011 ed.): Patricia Victor, Chris Cornelis, Martine de Cock Trust Networks for Recommender Systems (Paperback, 2011 ed.)
Patricia Victor, Chris Cornelis, Martine de Cock
R1,516 Discovery Miles 15 160 Ships in 10 - 15 working days

This book describes research performed in the context of trust/distrust propagation and aggregation, and their use in recommender systems. This is a hot research topic with important implications for various application areas. The main innovative contributions of the work are: -new bilattice-based model for trust and distrust, allowing for ignorance and inconsistency -proposals for various propagation and aggregation operators, including the analysis of mathematical properties -Evaluation of these operators on real data, including a discussion on the data sets and their characteristics. -A novel approach for identifying controversial items in a recommender system -An analysis on the utility of including distrust in recommender systems -Various approaches for trust based recommendations (a.o. base on collaborative filtering), an in depth experimental analysis, and proposal for a hybrid approach -Analysis of various user types in recommender systems to optimize bootstrapping of cold start users.

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