Articles liés à Probabilistic Matrix Factorization Based Collaborative...

Probabilistic Matrix Factorization Based Collaborative Filtering: Implicit Trust Derived From Review Ratings Information - Couverture souple

Ercan, Eda

 
9783846597545: Probabilistic Matrix Factorization Based Collaborative Filtering: Implicit Trust Derived From Review Ratings Information
Couverture souple
ISBN 10 : 3846597546 ISBN 13 : 9783846597545
Editeur : LAP LAMBERT Academic Publishing, 2011

Synopsis

Recommender systems aim to suggest relevant items that are likely to be of interest to the users using a variety of information resources such as user profiles, trust information and users past predictions. However, typical recommender systems suffer from poor scalability, generating incomprehensible and not useful recommendations and data sparsity problem.In this work, we have proposed a probabilistic matrix factorization based local trust boosted recommendation system which handles data sparsity, scalability and understandability problems. The method utilizes the implicit trust in the review ratings of users. The experiments conducted on Epinions.com dataset showed that our method compares favorably with the methods in the literature.In the scope of this work, we have analyzed the effect of latent vector initialization in matrix factorization models; different techniques are compared with the selected evaluation criteria.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Recommender systems aim to suggest relevant items that are likely to be of interest to the users using a variety of information resources such as user profiles, trust information and users past predictions. However, typical recommender systems suffer from poor scalability, generating incomprehensible and not useful recommendations and data sparsity problem.In this work, we have proposed a probabilistic matrix factorization based local trust boosted recommendation system which handles data sparsity, scalability and understandability problems. The method utilizes the implicit trust in the review ratings of users. The experiments conducted on Epinions.com dataset showed that our method compares favorably with the methods in the literature.In the scope of this work, we have analyzed the effect of latent vector initialization in matrix factorization models; different techniques are compared with the selected evaluation criteria.

Biographie de l'auteur

Eda Ercan has obtained her B.S. degree in Computer Engineering in 2007, and M.S. degree in Information Systems in 2010 both from Middle East Technical University. She continues to work for privately held companies.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2011
Langue
anglais
ISBN 10 
3846597546
ISBN 13 
9783846597545
Reliure
Broché
Nombre de pages
108
Coordonnées du fabricant
non disponible
Personne responsable
KreGa Onlinehandel GmbH
4950000000000
info@krega-onlinehandel.de

Birkenweg 31
Brakel
33034
Allemagne