A Browser for Large Knowledge Bases Based on a Hybrid Distributed/Local Connectionist Architecture

Tariq Samad, Peggy Israel

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

As the proliferation of expert systems continues, better aids for their construction and maintenance become increasingly important In particular, the browsing facilities provided by current expert system development tools have limited capabilities for handling large, complex knowledge bases. We have developed a browser concept, based on a connectionist architecture that utilizes both distributed and local representations, that overcomes some of these limitations. A proof-of-concept system has been implemented for an internally developed, Honeywell-proprietary knowledge acquisition tool. In our browser, concepts and relations in a knowledge base are represented using “microfeatures.” The microfeatures can encode semantic attributes, structural features, contextual information, etc. Desired portions of the knowledge base can then be associatively retrieved based on a structured cue. An ordered list of partial matches is presented to the user for selection. Microfeatures can also be used as “bookmarks”—they can be placed dynamically at appropriate points in the knowledge base and subsequently used as retrieval cues. The browser concept can be applied wherever there is a need for conveniently inspecting and manipulating structured information.

Original languageEnglish (US)
Pages (from-to)89-99
Number of pages11
JournalIEEE Transactions on Knowledge and Data Engineering
Volume3
Issue number1
DOIs
StatePublished - Mar 1991

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