Trust Networks for Recommender Systems [electronic resource] /
Victor, Patricia.author.
Cornelis, Chris.author.
De Cock, Martine.author.
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.
Description based upon print version of record.
Trust Networks for Recommender Systems; Foreword; Preface; Contents; 1 Introduction; 2 Trust Models; 3 Trust Propagation; 4 Trust Aggregation; 5 Social Recommender Systems; 6 Trust & Distrust-Based Recommendations; 7 Connection Guidancefor Cold Start Users; 8 Conclusions; Bibliography; Subject Index
Includes bibliographical references and index.
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.
Artificial intelligence.
Logic design.
Artificial Intelligence.
Logic Design.
Atlantis Computational Intelligence Systems