Machine Learning

, Volume 2, Issue 2, pp 139-172

First online:

Knowledge Acquisition Via Incremental Conceptual Clustering

  • Douglas H. Fisher


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.

Conceptual clustering concept formation incremental learning inference hill climbing