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Content-based software classification by self-organization | IEEE Conference Publication | IEEE Xplore

Content-based software classification by self-organization


Abstract:

This paper is concerned with a case study in content-based classification of textual documents. In particular we compare the application of two prominent self-organizing ...Show More

Abstract:

This paper is concerned with a case study in content-based classification of textual documents. In particular we compare the application of two prominent self-organizing neural networks to the same problem domain, namely the organization of software libraries. The two models are adaptive resonance theory and self-organizing maps. As a result we are able to show that both models successfully arrange software components according to their semantic similarity.
Date of Conference: 27 November 1995 - 01 December 1995
Date Added to IEEE Xplore: 06 August 2002
Print ISBN:0-7803-2768-3
Conference Location: Perth, WA, Australia

References

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