Acquisition of knowledge from data
Gio C. M. Wiederhold, M Walker, Robert L. Blum, Stephen M. Downs · 1986
The work described here addresses two problems: information overload of database users, and knowledge acquisition for use in Al systems. We have implemented programs that use artificial intelligence techniques to prepare high-level, intelligent summaries of databases, and that use empirical databases in turn, in combination with statistical and Al methods, to generate new domain knowledge base. Both programs are examples of the aquisition of knowledge from data: the Summarization Module fuses large amounts of data succinctly, the Discovery Module extracts new knowledge present implicitly in data. We describe the implementation of our programs and outline planned extensions which combine both approaches. This work is distinguished from current knowledge engineering approaches in that we prime the system with expert knowledge, and then use factual data to learn more about the domain.