Artificial Intelligence Lab, Department of MIS, University of Arizona / The results of a study that involved the creation of knowledge bases of concepts from large, operational textual
databases are reported. Two East-bloc computing knowledge
bases, both based on a semantic network structure, were created automatically using two statistical algorithms. With the help of four East-bloc computing experts, we evaluated the two knowledge bases in detail in a concept-association experiment based on recall and recognition tests. In the experiment, one of the knowledge bases that exhibited the asymmetric link property out-performed all four experts in recalling relevant concepts in East-bloc computing. The knowledge base, which contained about 20,O00 concepts (nodes) and 280,O00 weighted relationships
(links), was incorporated as a thesaurus-like component into an intelligent retrieval system. The system allowed users to perform semantics-based information management and information retrieval via interactive, conceptual relevance feedback.
Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/105175 |
Date | January 1992 |
Creators | Chen, Hsinchun, Lynch, K.J. |
Publisher | IEEE |
Source Sets | University of Arizona |
Language | English |
Detected Language | English |
Type | Journal Article (Paginated) |
Page generated in 0.0015 seconds