Table of ContentsLearning Ontologies in a Multiagent System for the World Wide Web Ontologies and the World Wide Web Domain Semantic Concept Interpretation Recursive Semantic Context Rule Learning (RSCRL) Recursive Semantic Context Rule Learning (cont.) Concept Cluster Integration (CCI) DOGGIE Distributed Ontology Gathering Group Integration Environment Agent Model Learning Fully Connected Network Disparate References to Concept Concept Translation Learning Fully Connected Network Recursive Semantic Context Rule Learning Fully Connected Network Different Vocabularies Query Forward / Concept Translation Query Forward / Concept Translation Summary |
Author: Andrew
B. Williams  Andrew B. Williams received the B.S. in Electrical Engineering in 1988 from the University of Kansas, the M.S. in Electrical & Computer Engineering in 1995 from Marquette University, and the Ph.D. in Electrical Engineering from the University of Kansas in 1999. He is currently an assistant professor in the Electrical & Computer Engineering Department at the University of Iowa. He previously worked at GE medical Systems and Allied Signal Aerospace Company. He also has internship experience at GE Corporate Research & Development and Lucent Technologies. Dr. Williams' research activities include developing multiagent learning algorithms for AI-assisted browsing and search for the World Wide Web. He has also worked on intelligent image classification and applied AI applications. Dr. Williams was a Patricia Roberts Harris Fellow in 1991 and a GEM Ph.D. Fellow sponsored by General Electric Company. |