An architecture and category knowledge for intelligent information retrieval agents

Information overload has become a serious problem for users of the World Wide Web. We propose to use intelligent information retrieval (IIR) agents as a solution to this problem. We identify the desirable features of an IIR agent, including intelligent search, navigation guide, auto notification, personal information management, personal preferred interface, and tools for easy page reading. A modularized agent architecture is then proposed. We describe the responsibility of each component and how they are combined to performed to the various tasks of the IIR agent. We point out that group knowledge, acquired from preferences of other users in the same group, may be useful. Knowledge of our agents is primarily represented by categories. After defining and clarifying the difference between clusters, directories and categories, we present category representations as an abstraction of certain desired information. Possible applications of category knowledge are also examined.