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dc.contributor.authorChen, Hsinchun
dc.contributor.authorLynch, K.J.
dc.date.accessioned2004-10-01T00:00:01Z
dc.date.available2010-06-18T23:20:36Z
dc.date.issued1992en_US
dc.date.submitted2004-10-01en_US
dc.identifier.citationAutomatic Construction of Networks of Concepts Characterizing Document Databases 1992, 22(5):885-902 IEEE Transactional on Systems, Man, and Cybermeticsen_US
dc.identifier.urihttp://hdl.handle.net/10150/105175
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractThe 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.
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectDatabasesen_US
dc.subjectArtificial Intelligenceen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherInformation retrievalen_US
dc.titleAutomatic Construction of Networks of Concepts Characterizing Document Databasesen_US
dc.typeJournal Article (Paginated)en_US
dc.identifier.journalIEEE Transactional on Systems, Man, and Cybermeticsen_US
refterms.dateFOA2018-08-21T10:11:40Z
html.description.abstractThe 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.


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