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An MHP framework to provide intelligent personalized recommendations about digital TV contents

Abstract:

Digital Television will bring a significant increase in the amount of channels and programs available to end users, with many more difficulties to find contents appealing to them among a myriad of irrelevant information. Thus, automatic content recommenders should receive special attention in the following years to improve their assistance to users. The current content recommenders have important deficiencies that hamper their wide acceptance. In this paper, we present a new approach for automatic content recommendation that significantly reduces those deficiencies. This approach, based on Semantic Web technologies, has been implemented in the AdVAnced Telematic search of Audiovisual contents by semantic Reasoning tool, a hybrid content recommender that makes extensive use of well-known standards, such as Multimedia Home Platform, TV-Anytime and OWL. Also, we have carried out an experimental evaluation, the results of which show that our proposal performs better than other existing approaches. Copyright © 2007 John Wiley & Sons, Ltd.