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Hybrid recommender for multimedia item recommendation: Development of a hybrid content-collaborative recommender system for multimedia item recommendation - Couverture souple
Synopsis
User modeling is a procedure used to filter available content in order to present the user with a selection of interesting items. Systems performing this procedure are known as recommenders. This work presents the development of two different recommenders that were evaluated using two very different datasets. The recommenders were evaluated using the F-measure metric, which frequently used in the field of user modeling. During the development of our first system we focused on collaborative recommenders that are based on the nearest neighbor search. We tested two methods for nearest neighbor selection and two methods for calculating predicted ratings. Based on our results we developed a new method – adjusted weighted sum. The first recommender system performed efficiently, but required a lot of time to create a list of recommendations for a single user. In order to correct this we developed a new, hybrid recommender. We expanded existing user profiles by adding genre preferences that were used to select nearest neighbors. The new system worked noticeably faster while still maintaining a high level of efficiency.
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À propos de l?auteur
Matevž Kunaver, PhD researcher at the University of Ljubljana(UL), research interests cover recommender systems and user personalization. Andrej Košir, PhD, professor at UL, research areas include operational research and user personalization. Jurij Tasič, PhD, professor of system theory and computing at UL.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurLAP Lambert Academic Publishing
- Date d'édition2011
- ISBN 10 3847304100
- ISBN 13 9783847304104
- ReliureBroché
- Langueanglais
- Nombre de pages136
- Coordonnées du fabricantnon disponible
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Hybrid recommender for multimedia item recommendation: Development of a hybrid content-collaborative recommender system for multimedia item recommendation
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LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3847304100
ISBN 13 : 9783847304104
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Couverture souple
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Hybrid recommender for multimedia item recommendation
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3847304100
ISBN 13 : 9783847304104
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Couverture souple
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Hybrid recommender for multimedia item recommendation : Development of a hybrid content-collaborative recommender system for multimedia item recommendation
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3847304100
ISBN 13 : 9783847304104
Neuf
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - User modeling is a procedure used to filter available content in order to present the user with a selection of interesting items. Systems performing this procedure are known as recommenders. This work presents the development of two different recommenders that were evaluated using two very different datasets. The recommenders were evaluated using the F-measure metric, which frequently used in the field of user modeling. During the development of our first system we focused on collaborative recommenders that are based on the nearest neighbor search. We tested two methods for nearest neighbor selection and two methods for calculating predicted ratings. Based on our results we developed a new method adjusted weighted sum. The first recommender system performed efficiently, but required a lot of time to create a list of recommendations for a single user. In order to correct this we developed a new, hybrid recommender. We expanded existing user profiles by adding genre preferences that were used to select nearest neighbors. The new system worked noticeably faster while still maintaining a high level of efficiency. N° de réf. du vendeur 9783847304104
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Hybrid recommender for multimedia item recommendation
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LAP LAMBERT Academic Publishing Dez 2011, 2011
ISBN 10 : 3847304100
ISBN 13 : 9783847304104
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -User modeling is a procedure used to filter available content in order to present the user with a selection of interesting items. Systems performing this procedure are known as recommenders. This work presents the development of two different recommenders that were evaluated using two very different datasets. The recommenders were evaluated using the F-measure metric, which frequently used in the field of user modeling. During the development of our first system we focused on collaborative recommenders that are based on the nearest neighbor search. We tested two methods for nearest neighbor selection and two methods for calculating predicted ratings. Based on our results we developed a new method adjusted weighted sum. The first recommender system performed efficiently, but required a lot of time to create a list of recommendations for a single user. In order to correct this we developed a new, hybrid recommender. We expanded existing user profiles by adding genre preferences that were used to select nearest neighbors. The new system worked noticeably faster while still maintaining a high level of efficiency. 136 pp. Englisch. N° de réf. du vendeur 9783847304104
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Hybrid recommender for multimedia item recommendation
Edité par
LAP LAMBERT Academic Publishing Dez 2011, 2011
ISBN 10 : 3847304100
ISBN 13 : 9783847304104
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. Neuware -User modeling is a procedure used to filter available content in order to present the user with a selection of interesting items. Systems performing this procedure are known as recommenders. This work presents the development of two different recommenders that were evaluated using two very different datasets. The recommenders were evaluated using the F-measure metric, which frequently used in the field of user modeling. During the development of our first system we focused on collaborative recommenders that are based on the nearest neighbor search. We tested two methods for nearest neighbor selection and two methods for calculating predicted ratings. Based on our results we developed a new method ¿ adjusted weighted sum. The first recommender system performed efficiently, but required a lot of time to create a list of recommendations for a single user. In order to correct this we developed a new, hybrid recommender. We expanded existing user profiles by adding genre preferences that were used to select nearest neighbors. The new system worked noticeably faster while still maintaining a high level of efficiency.Books on Demand GmbH, Überseering 33, 22297 Hamburg 136 pp. Englisch. N° de réf. du vendeur 9783847304104
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Hybrid recommender for multimedia item recommendation: Development of a hybrid content-collaborative recommender system for multimedia item recommendation
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3847304100
ISBN 13 : 9783847304104
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