Hybrid Recommender System for Web Usage Mining - Couverture souple

Mukkamula, Venu Gopalachari

 
9783330055568: Hybrid Recommender System for Web Usage Mining
Couverture souple
ISBN 10 : 3330055561 ISBN 13 : 9783330055568
Editeur : LAP LAMBERT Academic Publishing, 2017

Synopsis

Recommender System is a wide area that has many sub fields that require a deep understanding and great research efforts. In particular the main aspects are: information inputs that are used by the algorithm that impacts the recommendations, algorithms that are hidden background and run the recommendation engine to predict the user’s preferences, evaluation metrics that defines the satisfaction of the user and the quality of the recommendations.The sole dependency on user profile based on navigation history alone cannot promise the quality of recommendations in terms of accuracy and diversity because of lack of semantics in the processing. The time parameter in recommender systems should be considered on top of conceptual semantics as it has a great influence on item’s popularity and user’s preferences. The traditional evaluating metrics could not able to deal cold-start problem, that occurs with new users and new or less popular items in the web domain, because of the traditional filtering methods that mix up all users and items with same intent.

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

Présentation de l'éditeur

Recommender System is a wide area that has many sub fields that require a deep understanding and great research efforts. In particular the main aspects are: information inputs that are used by the algorithm that impacts the recommendations, algorithms that are hidden background and run the recommendation engine to predict the user’s preferences, evaluation metrics that defines the satisfaction of the user and the quality of the recommendations.The sole dependency on user profile based on navigation history alone cannot promise the quality of recommendations in terms of accuracy and diversity because of lack of semantics in the processing. The time parameter in recommender systems should be considered on top of conceptual semantics as it has a great influence on item’s popularity and user’s preferences. The traditional evaluating metrics could not able to deal cold-start problem, that occurs with new users and new or less popular items in the web domain, because of the traditional filtering methods that mix up all users and items with same intent.

Biographie de l'auteur

Venu Gopalachari is an academician from India. He obtained PhD in web usage mining and semantic web at JNTUH University in 2017.

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
2017
Langue
anglais
ISBN 10 
3330055561
ISBN 13 
9783330055568
Reliure
Broché
Nombre de pages
108
Coordonnées du fabricant
non disponible
Personne responsable
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