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Comparison of approximated paths in search of similarities for the JSM method

Comparison of approximated paths in search of similarities for the JSM method This paper reports on possible solutions to problems arising in work with the JSM method of automated hypothesis generation with large arrays of data. To diminish the power of the set of JSM hypotheses, an algorithm that uses the evolutionary model is suggested. Comparison is made between various approaches to optimization tasks and conditions for their application. The results from testing the algorithms on real data are presented. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Automatic Documentation and Mathematical Linguistics Springer Journals

Comparison of approximated paths in search of similarities for the JSM method

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Publisher
Springer Journals
Copyright
Copyright © 2010 by Allerton Press, Inc.
Subject
Computer Science; Information Storage and Retrieval
ISSN
0005-1055
eISSN
1934-8371
DOI
10.3103/S000510551006004X
Publisher site
See Article on Publisher Site

Abstract

This paper reports on possible solutions to problems arising in work with the JSM method of automated hypothesis generation with large arrays of data. To diminish the power of the set of JSM hypotheses, an algorithm that uses the evolutionary model is suggested. Comparison is made between various approaches to optimization tasks and conditions for their application. The results from testing the algorithms on real data are presented.

Journal

Automatic Documentation and Mathematical Linguistics – Springer Journals

Published: Feb 6, 2011

References

  • Genetic Algorithms
    Gladkov, L.A.; Kureychik, V.V.; Kureychik, V.M.
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