Trust Networks for Recommender Systems (Atlantis Computational Intelligence Systems, 4)

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. Annotation 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 Front Matter....Pages i-xiii Introduction....Pages 1-7 Trust Models....Pages 9-22 Trust Propagation....Pages 23-50 Trust Aggregation....Pages 51-90 Social Recommender Systems....Pages 91-107 Trust and Distrust-Based Recommendations....Pages 109-153 Connection Guidance for Cold Start Users....Pages 155-187 Conclusions....Pages 189-191 Back Matter....Pages 193-202