A Model of Collaborating Agents for Content-Based Electronic Document Filtering

The huge volume of distributed information that is nowadays available in electronic multimedia documents forces a lot of people to consume a significant percentage of their time looking for documents that contain information useful to them. The filtering of electronic documents seems hard to automate, partly because of document heterogeneity, but mainly because it is difficult to train computers to have an understanding of the contents of these documents and make decisions based on user-subjective criteria. In this paper, we suggest a model for the automation of content-based electronic document filtering, supporting multimedia documents in a wide variety of forms. The model is based on multi-agent technology and utilizes an adaptive knowledge base organized as a set of logical rules. Implementations of the model using the client-server architecture should be able to efficiently access documents distributed over an intranet or the Internet.