Supporting Context-Aware Media Recommendations for Smart Phones
IEEE Pervasive Computing
Reinforcement learning for dynamic multimedia adaptation
Journal of Network and Computer Applications
A framework for designing personalized ubiquitous multimedia
Proceedings of the 12th international conference on Entertainment and media in the ubiquitous era
UIC'06 Proceedings of the Third international conference on Ubiquitous Intelligence and Computing
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This paper discusses a new approach of generating TV-like multimedia presentations that are adapted to the target user preferences and to limited devices. Three main points are discussed: 1) the encoding of video presentations from a SMIL specification, 2) the adaptation of the video content based on the user preferences, and 3) the delivery of adapted multimedia presentations. The used architecture includes a content server, an adaptation proxy and a set of small devices in the form of personal device assistants (PDA). These devices request the content through a wireless network. In order to show how the system behaves regarding the user preferences and capabilities, two negotiation dimensions are considered: the user language and the memory capability of the device. The first dimension is used to generate a content that can be understood by the target user, e.g. a video with subtitles written in the preferred language. The second dimension is chosen to solve the problem of the system blocking that usually happens when limited devices access rich multimedia presentations over the network.