TiVo: making show recommendations using a distributed collaborative filtering architecture
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Multimedia Tools and Applications
Towards Semantics-Based Instantiation of Services
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
A recommender handoff framework for a mobile device
Mobile Multimedia Processing
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With the steadily increasing amount of digital multimedia content, the user will be more and more overstrained. This applies to content being permanently available like videos of online video services as well as broadcast content like in the TV or radio domain. A promising solution for this problem is personalization. In the context of this paper, we refer to the selection and recommendation of content with respect to user's interests and preferences as personalization. These recommendations can either be presented to the user herself or be further used by services like a personalized electronic program guide (EPG) in the TV domain or for automated and personalized selection of content of online video services. This paper introduces an approach to personalize digital multimedia content based on user profile information. For this, two main mechanisms were developed: a profile generator that automatically creates user profiles representing the user preferences, and a content-based recommendation algorithm that estimates the user's interest in unknown content by matching her profile to metadata descriptions of the content. Both features are integrated into a personalization system.