International audienceThis paper surveys the landscape of actual personalized TV recommender systems, and introduces challenges on context-awareness and viewer behavior prediction applied to social TV-recommender systems. Real data related to the viewers behaviors and the social context have been picked up in real-time through a social TV platform. We highlighted the future benefits of analyzing viewer behavior and exploiting the social influence on viewers’s preferences to improve recommendation in respect with TV contents’ change
Recommender systems alleviate the problem of searching for interesting content in the iTV do- main ...
Today’s IP-based TV services commonly strive for personalizing their content offers using complex re...
AbstractIn the area of intelligent systems, research about recommender systems is a critical topic a...
Context-awareness has become a critical factor to improve the prediction of user interest in modern ...
Context-awareness has become a critical factor in improving the predictions of user interest in mode...
International audienceDue to the diversity of alternative programs to watch and the change of viewer...
Context-awareness has become a critical factor in improving the predictions of user interest in mode...
In this paper, we present a better understanding of the contextual aspects that determine TV and vid...
The recommender systems are deployed on the Web for reducing cognitive overload. It uses different p...
In this workshop paper we provide an overview of our research activities and results in the TV-RING ...
This paper contains development of methods of improving TV-watching experience using Machine Learnin...
Contexts and social web information have been recognized to be valuable information for making perfe...
The enormous offer of video content on the internet and its continuous growth make the selection pro...
The problem of information overloading is prevalent in recommendations websites and social networks....
Switching through the variety of available TV channels to find the most acceptable program at the cu...
Recommender systems alleviate the problem of searching for interesting content in the iTV do- main ...
Today’s IP-based TV services commonly strive for personalizing their content offers using complex re...
AbstractIn the area of intelligent systems, research about recommender systems is a critical topic a...
Context-awareness has become a critical factor to improve the prediction of user interest in modern ...
Context-awareness has become a critical factor in improving the predictions of user interest in mode...
International audienceDue to the diversity of alternative programs to watch and the change of viewer...
Context-awareness has become a critical factor in improving the predictions of user interest in mode...
In this paper, we present a better understanding of the contextual aspects that determine TV and vid...
The recommender systems are deployed on the Web for reducing cognitive overload. It uses different p...
In this workshop paper we provide an overview of our research activities and results in the TV-RING ...
This paper contains development of methods of improving TV-watching experience using Machine Learnin...
Contexts and social web information have been recognized to be valuable information for making perfe...
The enormous offer of video content on the internet and its continuous growth make the selection pro...
The problem of information overloading is prevalent in recommendations websites and social networks....
Switching through the variety of available TV channels to find the most acceptable program at the cu...
Recommender systems alleviate the problem of searching for interesting content in the iTV do- main ...
Today’s IP-based TV services commonly strive for personalizing their content offers using complex re...
AbstractIn the area of intelligent systems, research about recommender systems is a critical topic a...