VideoZapper: A System for Delivering Personalized Video Content
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Given the huge amounts of audiovisual materials that are broadcasted every day there is considerable interest in applications that are able to fulfill our need for selecting information. In this paper, we propose a system, VideoZapper, which can personalize and help to select audiovisual content based on its properties (represented as metadata descriptors) and mainly on the past experience of other users with that material. The content is selected based on the user profile and the description of each of the segments to be presented. A second level of selection is based on a “virtual edition” of the content, taking into account what previous users/viewers did. The paper presents related personalization and metadata approaches, the rational and principles for continuous media personalization, our current architecture and system, and preliminary experiences.
Keywordspersonalized video editing rules video servers metadata
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