Philip S. Yu

Work place: College of Engineering, University of Illinois, IL, USA King Abdulaziz University, Jeddah, Saudi Arabia

E-mail: psyu@cs.uic.edu

Website:

Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Data Mining, Data Structures and Algorithms

Biography

Philip S. Yu is a Professor in Computer Science at the University of Illinois at Chicago and also holds the Wexler Chair in Information Technology.   Dr. Yu spent most of his career at IBM, where he was manager of the Software Tools and Techniques group at the Watson Research Center. His research interest is on big data, including data mining, data stream, database and privacy. He has published more than 730 papers in refereed journals and conferences. He holds or has applied for more than 250 US patents. Dr. Yu is a Fellow of the ACM and the IEEE.  He is the Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data. Dr. Yu received the B.S. Degree in E.E. from National Taiwan University, the M.S. and Ph.D. degrees in E.E. from Stanford University, and the M.B.A. degree from New York University.

Author Articles
Discovery of Association Rules from University Admission System Data

By Abdul Fattah Mashat Mohammed M. Fouad Philip S. Yu Tarek F. Gharib

DOI: https://doi.org/10.5815/ijmecs.2013.04.01, Pub. Date: 8 Apr. 2013

Association rules discovery is one of the vital data mining techniques. Currently there is an increasing interest in data mining and educational systems, making educational data mining (EDM) as a new growing research community. In this paper, we present a model for association rules discovery from King Abdulaziz University (KAU) admission system data. The main objective is to extract the rules and relations between admission system attributes for better analysis. The model utilizes an apriori algorithm for association rule mining. Detailed analysis and interpretation of the experimental results is presented with respect to admission office perspective.

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