Knowledge base browsing. An application of hybrid distributed/local connectionist networks

Tariq Samad, Peggy Israel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We describe a knowledge base browser based on a connectionist (or neural network) architecture that employs both distributed and local representations. The distributed representations are used for input and output, thereby enabling associative, noise-tolerant interaction with the environment. Internally, all representations are fully local. This simplifies weight assignment and facilitates network configuration for specific applications. 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. A proof-of-concept system has been implemented for an internally developed, Honeywell-proprietary knowledge acquisition tool.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsSteven K. Rogers
PublisherPubl by Int Soc for Optical Engineering
Pages404-415
Number of pages12
ISBN (Print)0819403458
StatePublished - Dec 1 1990
EventApplications of Artificial Neural Networks - Orlando, FL, USA
Duration: Apr 18 1990Apr 20 1990

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume1294
ISSN (Print)0277-786X

Other

OtherApplications of Artificial Neural Networks
CityOrlando, FL, USA
Period4/18/904/20/90

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