Victor, Patricia.
Trust Networks for Recommender Systems [electronic resource] / by Patricia Victor, Chris Cornelis, Martine de Cock. - XIV, 202 p. online resource. - Atlantis Computational Intelligence Systems, 4 1875-7650 ; . - 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.
9789491216084
10.2991/978-94-91216-08-4 doi
Computer science.
Logic design.
Artificial intelligence.
Computer Science.
Artificial Intelligence (incl. Robotics).
Logic Design.
Q334-342 TJ210.2-211.495
006.3
Trust Networks for Recommender Systems [electronic resource] / by Patricia Victor, Chris Cornelis, Martine de Cock. - XIV, 202 p. online resource. - Atlantis Computational Intelligence Systems, 4 1875-7650 ; . - 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.
9789491216084
10.2991/978-94-91216-08-4 doi
Computer science.
Logic design.
Artificial intelligence.
Computer Science.
Artificial Intelligence (incl. Robotics).
Logic Design.
Q334-342 TJ210.2-211.495
006.3