Proceedings

An Application of AI Techniques to Structuring Objects into an Optimal Conceptual Hierarchy

Download BibTeX Cite

Proceedings of the Seventh International Joint Conference on Artificial Intelligence. Theoretical Foundations. Pages 460-464.

Abstract

A aethod of "learning froa obaervation" 1a preaented which atructurea a collection of objecta into hierarchlea of aubcategoriea, auch that each aubcategory ia characteriaed by a conjunctive deacription involving relatione on aelected object attribute&. The conjunctive deacriptiona aprouting froa each node are ~tually diajoint and optimal aa a group accordiQ& to a flexibly defined criterion. Each level of the hierarchy ia deterained by an iterative proceaa which repetitively applies a veraion of the A* aearch algoritha. Experiaenta with the prograa CLUSTEI/PAF iaplementing the method indicate that the obtained hierarchiea represent aolutiona which have a aiaple conceptual interpretation and which aeea to agree well with the way people atructure objecta.

Ryszard S. Michalski, and Robert E. Stepp. 1981. An Application of AI Techniques to Structuring Objects into an Optimal Conceptual Hierarchy. In Proceedings of the Seventh International Joint Conference on Artificial Intelligence, IJCAI-81. IJCAI, 460–464. https://ijcai.org/proceedings/1981/89
Welcome Future Conferences AI Journal Division IJCAI Proceedings About IJCAI IJCAI Awards