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1 August 1990 Knowledge-base browsing: an application of hybrid distributed/local connectionist networks
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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. 1.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tariq Samad and Peggy Israel "Knowledge-base browsing: an application of hybrid distributed/local connectionist networks", Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); https://doi.org/10.1117/12.21192
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