Document (#11273)

Author
Chen, H.
Ng, T.
Title
¬An algorithmic approach to concept exploration in a large knowledge network (automatic thesaurus consultation) : symbolic branch-and-bound search versus connectionist Hopfield Net Activation
Source
Journal of the American Society for Information Science. 46(1995) no.5, S.348-369
Year
1995
Abstract
Presents a framework for knowledge discovery and concept exploration. In order to enhance the concept exploration capability of knowledge based systems and to alleviate the limitation of the manual browsing approach, develops 2 spreading activation based algorithms for concept exploration in large, heterogeneous networks of concepts (eg multiple thesauri). One algorithm, which is based on the symbolic AI paradigma, performs a conventional branch-and-bound search on a semantic net representation to identify other highly relevant concepts (a serial, optimal search process). The 2nd algorithm, which is absed on the neural network approach, executes the Hopfield net parallel relaxation and convergence process to identify 'convergent' concepts for some initial queries (a parallel, heuristic search process). Tests these 2 algorithms on a large text-based knowledge network of about 13.000 nodes (terms) and 80.000 directed links in the area of computing technologies
Theme
Konzeption und Anwendung des Prinzips Thesaurus
Inhaltsanalyse
Object
Hopfield-Netze
Aid
Hopfield-Netze

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  5. Zhang, W.; Korf, R.E.: Performance of linear-space search algorithms (1995) 0.12
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