Ubiquitous media agents: a framework for managing personally accumulated multimedia files
A novel idea and framework of ubiquitous media agents is presented for managing personal multimedia objects. Media agents are intelligent systems that can autonomously do the following tasks. They automatically collect and build personalized semantic indices of multimedia data on behalf of the user whenever and wherever he accesses/uses these multimedia data. The sources of these semantic descriptions are the textual context of the same documents that contain these multimedia data. The URLs of these multimedia data are indexed using these textual features. When the user wants to use these multimedia data again, the media agents can help the user find relevant multimedia data and provide proper suggestions based on the semantic indices. The media agents learn from the user's interaction records to refine the semantic indices and to model user intentions and preferences. Various algorithms can be used to implement the framework, and a few of them are described in this paper. As shown in the experiments, the media agents are effective in gathering relevant semantics for media objects and learning to provide precise suggestions when the user wants to reuse relevant media objects again.
agent personalization learning multimedia information management personal media management user adaptation natural language processing