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Knowledge acquisition via incremental conceptual clustering (1987)
| Venue: | Machine Learning |
| Citations: | 759 - 9 self |
BibTeX
@INPROCEEDINGS{Fisher87knowledgeacquisition,
author = {Douglas H. Fisher},
title = {Knowledge acquisition via incremental conceptual clustering},
booktitle = {Machine Learning},
year = {1987},
pages = {139--172}
}
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Abstract
hill climbing 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. 1.
