Knowledge acquisition via incremental conceptual clustering View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

1987-09

AUTHORS

Douglas H. Fisher

ABSTRACT

Conceptual clustering is an important way of summarizing and explaining data. However, the recent formulation of this paradigm has allowed little exploration of conceptual clustering as a means of improving performance. Furthermore, previous work in conceptual clustering has not explicitly dealt with constraints imposed by real world environments. This article presents COBWEB, a conceptual clustering system that organizes data so as to maximize inference ability. Additionally, COBWEB is incremental and computationally economical, and thus can be flexibly applied in a variety of domains. More... »

PAGES

139-172

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf00114265

DOI

http://dx.doi.org/10.1007/bf00114265

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1017000685


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