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.

One characteristic of intelligence is adaptation. Computers should adapt to who is using them, how, why, when and where. The computer's representation of the user is called a user model; user modeling is concerned with developing techniques for representing the user and acting upon this information. The Doppelg anger system consists of a set of techniques for gathering, maintaining, and acting upon information about individuals, and illustrates my approach to user modeling. Work on Doppelg anger has been heavily influenced by the field of machine learning. This thesis has a twofold purpose: first, to set forth guidelines for the integration of machine learning techniques into user modeling, and second, to identify particular user modeling tasks for which machine learning is useful.