Conjunctive Conceptual Clustering: A Methodology and Experimentation (Learning)

This thesis describes a machine learning methodology called conjunctive conceptual clustering. The methodology can find conceptual patterns in data as illustrated by three sample problems. In one problem, the method is used to rediscover categories of soybean disease when given a collection of 47 descriptions of diseased soybeans having one of four diseases. In a second problem, the method is used to find categories underlying a collection of blocks-world structures. In a third problem, categories of objects having a more complex structure are determined and contrasted with categories generated by people.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2014

Author dc:creator

• Stepp, Robert Earl, III

• Computer Science

Identifier

(UMI)AAI8502306

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/69539