Constraints on Tree Structure in Concept Formation

We describe ARACHNE, a concept formation system that, uses explicit constraints on tree structure and local restructuring operators to produce well-formed probabilistic concept trees. We also present a quantitative measure of tree quality and compare the system's performance in artificial and natural domains to that of COBWEB, a well-known concept formation algorithm. The results suggest that ARACHNE frequently constructs higher-quality trees than COBWEB, while still retaining the ability to make accurate predictions.