Fr. 69.00

Trust Networks for Recommender Systems

English · Paperback / Softback

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Description

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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.

Summary

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.

Product details

Authors Chri Cornelis, Chris Cornelis, Martine De Cock, Patrici Victor, Patricia Victor
Publisher Springer, Berlin
 
Languages English
Product format Paperback / Softback
Released 06.06.2013
 
EAN 9789491216398
ISBN 978-94-91-21639-8
No. of pages 202
Dimensions 157 mm x 237 mm x 11 mm
Weight 341 g
Illustrations XIII, 202 p.
Series Atlantis Computational Intelligence Systems
Atlantis Computational Intelligence Systems
Subject Natural sciences, medicine, IT, technology > IT, data processing > IT

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