Abstract
With the growth of online TV, people increasingly expect services like recommending and sharing in digital video libraries. The amount and diversity of online video is increasing rapidly, changing how people engage with TV content. Thus, there is a need for models that account for the new online TV systems and the evolving expectations of users. This paper reports on the first iteration of a digital library model for online TV. The model was developed experimentally by analyzing collections, services and temporal behaviors of the most popular online TV sites.
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