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Abstract:
This paper describes CitePack, an autonomous, agent-based system for automatically discovering resources based on learned user preferences. We discuss the need for a tool that can find information for a user without direct intervention, followed by the architecture of CitePack. We discuss the collection of related documents, and the construction of a user model based up support vector machines, which allows us to both learn a user's tastes and also recommend similar users. We conclude by discussing potential future directions.