Towards Mutual Understanding - An Overview on Ontologies, Ontology-Matching,
and their Applications
|Author:||Jingshan Huang University of South Alabama|
|Date:||May 21, 2010|
Ontologies are a formal knowledge representation model, and they have been widely adopted in many different disciplines and domains, e.g., the Semantic Web, Digital Forensics, and Medical Informatics. However, the heterogeneity issue inherent in ontologies needs to be handled well before information from different parties can be integrated, which is the basis to generate critical knowledge. In this presentation, the concept of ontologies along with the research motivation for ontology matching/alignment will be discussed in details, followed by an introduction of an innovative learning-based ontology-matching algorithm. Finally, some ongoing research efforts will be reported, including applying ontological techniques in the domains of Medical Informatics and Digital Forensics.
Dr. Jingshan Huang is an Assistant Professor of Computer Science in the School of Computer and Information Sciences at the University of South Alabama. He earned his Ph.D. degree in Computer Science from the University of South Carolina in 2007. His research interests include machine intelligence, knowledge representation, bioinformatics, and cognitive science. Prior to his current position, Dr. Huang was a faculty member at Benedict College, and a research scientist at the Medical University of South Carolina. He is a Full Member of Sigma Xi, the Scientific Research Society (inducted 2007), and he has served as a program committee member for many international conferences (e.g., AAMAS, ODBASE, and CIT).