Agentized, Contextualized Filters for Information Management

David A. Evans, Gregory Grefenstette, Yan Qu, James G. Shanahan, and Victor M. Sheftel

Every time a user engaged in work reads or writes, the user spontaneously generates new information needs: to understand the text he or she is reading or to supply more substance to the arguments he or she is creating. Simultaneously, each Information Object (IO) (i.e., word, entity, term, concept, phrase, proposition, sentence, paragraph, section, document, collection, etc.) encountered or produced creates context for the other IOs in the same discourse. We present a conceptual model of Agentized, Contextualized Filters (ACFs) -- agents that identify an appropriate context for an information object and then actively fetch and filter relevant information concerning the information object in other information sources the user has access to. We illustrate the use of ACFs in a prototype knowledge management system called ViviDocs.

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