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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