Automatic Association Rule Generation: From A Cognitive Informatics Perspective

Taehyung Wang: Department of Computer Science, California State University Northridge, CA, 91330, USA. (TEL) +1-818-677-3881 (FAX) +1-818-677-7208 (E-Mail) twang@csun.edu (URL) http://www.csun.edu/~twang

Wei Zhang: Department of EECS, University of California, Irvine, 92697, USA, (TEL) +1-949-824-2228 (E-Mail) wzhang@ece.uci.edu

Abstract

Learning is one of the higher cognitive functions of the brain. According to a layered model of Cognitive Informatics, an association rule is one of methods for learning knowledge. Thus, learning and association rules (e.g. data mining) have common high-level goals: prediction, validation, and learning of knowledge. Although many algorithms for the association rules are currently available, these algorithms for discovering association rules suffer severe performance degradation. In this paper, we introduce a novel method that automatically generates multi-dimensional association rules with high accuracy and board coverage.

Short Biography

Taehyung Wang: Taehyung Wang is an assistant professor in the Department of Computer Science at California State University Northridge (CSUN). His research interests include cognitive informatics, biomedical information system, software engineering, data mining, data warehousing, object-oriented design and analysis methodology, location-based service, data visualization, and web technologies.

Before joining CSUN, he worked as a researcher for the Visual Interactive Data Engineering Lab and the Center of Bioengineering at the University of California, Irvine. Dr. Wang received a Ph.D. degree in the University of California at Irvine in 1998, and he received a M.S. in Computer Science from Western Illinois University and a B.S. in Control and Instrumentation from Seoul National University in 1985, respectively.