Evaluating a recommendation application for online video content: an interdisciplinary study
Proceedings of the 8th international interactive conference on Interactive TV&Video
Information Sciences: an International Journal
Mobile Networks and Applications
Users' (Dis)satisfaction with the personalTV application: Combining objective and subjective data
Computers in Entertainment (CIE) - Theoretical and Practical Computer Applications in Entertainment
Expert Systems with Applications: An International Journal
A cloud-based intelligent TV program recommendation system
Computers and Electrical Engineering
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With the expansion of digital networks and TV devices and the rapid increase of the number of channels, people are exposed to an information overload, due to the presence of several hundreds of alternative programs to watch. In this context, personalization is achieved with the employment of algorithms and data collection schemes that predict and recommend to television viewers content that match their interests and/or needs. This paper introduces queveo.tv: a personalized TV program recommendation system. The proposed hybrid approach (combining content-filtering techniques with those based on collaborative filtering) also provides all typical advantages of any social network as comments, tagging, ratings, etc. This web 2.0 application has been devised to enormously simplify the task of selecting what program to watch on TV.