The growth of the Web 2.0 has brought to a widespread use of social media systems and to an increasing number of active users. This phenomenon implies that each user interacts with too many users and is overwhelmed by a huge amount of content, leading to the well know "social interaction overload" problem. In order to address this problem several research communities study Social Recommender Systems, which are information filtering systems that operate in the social media domain and aim at suggesting to the users items that are supposed to be interesting for them. This book proposes some social recommendation approaches based on the mining of the user behavior, i.e., on the exploitation of the activity of the users in social environments, in order to produce accurate and up-to-date recommendations.
"Sinopsis" puede pertenecer a otra edición de este libro.
The growth of the Web 2.0 has brought to a widespread use of social media systems and to an increasing number of active users. This phenomenon implies that each user interacts with too many users and is overwhelmed by a huge amount of content, leading to the well know "social interaction overload" problem. In order to address this problem several research communities study Social Recommender Systems, which are information filtering systems that operate in the social media domain and aim at suggesting to the users items that are supposed to be interesting for them. This book proposes some social recommendation approaches based on the mining of the user behavior, i.e., on the exploitation of the activity of the users in social environments, in order to produce accurate and up-to-date recommendations.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The growth of the Web 2.0 has brought to a widespread use of social media systems and to an increasing number of active users. This phenomenon implies that each user interacts with too many users and is overwhelmed by a huge amount of content, leading to the well know social interaction overload problem. In order to address this problem several research communities study Social Recommender Systems, which are information filtering systems that operate in the social media domain and aim at suggesting to the users items that are supposed to be interesting for them. This book proposes some social recommendation approaches based on the mining of the user behavior, i.e., on the exploitation of the activity of the users in social environments, in order to produce accurate and up-to-date recommendations. 116 pp. Englisch. Nº de ref. del artículo: 9783659684593
Cantidad disponible: 2 disponibles
Librería: moluna, Greven, Alemania
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Manca MatteoMatteo Manca earned his Ph.D. in CS from the University of Cagliari in May 2014. His interests include Social Recommender Systems and Machine Learning. Ludovico Boratto is a postdoc of the University of Cagliari. His inte. Nº de ref. del artículo: 15939348
Cantidad disponible: Más de 20 disponibles
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The growth of the Web 2.0 has brought to a widespread use of social media systems and to an increasing number of active users. This phenomenon implies that each user interacts with too many users and is overwhelmed by a huge amount of content, leading to the well know ¿social interaction overload¿ problem. In order to address this problem several research communities study Social Recommender Systems, which are information filtering systems that operate in the social media domain and aim at suggesting to the users items that are supposed to be interesting for them. This book proposes some social recommendation approaches based on the mining of the user behavior, i.e., on the exploitation of the activity of the users in social environments, in order to produce accurate and up-to-date recommendations.Books on Demand GmbH, Überseering 33, 22297 Hamburg 116 pp. Englisch. Nº de ref. del artículo: 9783659684593
Cantidad disponible: 1 disponibles
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The growth of the Web 2.0 has brought to a widespread use of social media systems and to an increasing number of active users. This phenomenon implies that each user interacts with too many users and is overwhelmed by a huge amount of content, leading to the well know social interaction overload problem. In order to address this problem several research communities study Social Recommender Systems, which are information filtering systems that operate in the social media domain and aim at suggesting to the users items that are supposed to be interesting for them. This book proposes some social recommendation approaches based on the mining of the user behavior, i.e., on the exploitation of the activity of the users in social environments, in order to produce accurate and up-to-date recommendations. Nº de ref. del artículo: 9783659684593
Cantidad disponible: 1 disponibles