Yun Sing Koh

After completing a Bachelor's degree in Computer Science and Masters in Software Engineering in University Malaya, I went on to do my PhD in Computer Science in Otago, New Zealand. I am currently a Lecturer in Computer Science at AUT University in New Zealand. My current research interests include: data mining, machine learning, and information retrieval.

 

Most of my current research revolves around finding rare patterns/rules within datasets. The aim is to find expensive rules that are of significance for users. I have been looking at different ways to generate rare association rules. I have also developed a keen interest in several other areas including particle swarm optimization and online auction fraud detection.

Contact

Dr Yun Sing Koh

School of Computing and Mathematical Sciences

Private Bag 92006

Auckland 1142

New Zealand.

ykoh@aut.ac.nz

 

PUBLICATIONS

International Refereed Conference Proceedings
S. Hoeglinger, R. Pears, and Y. S. Koh (2009). CBDT: A Concept Based Approach to Data Stream Mining, PAKDD 2009.
Y.S. Koh and R. Pears (2008). Rare Association Rule Mining via Transaction Clustering, in Australasian Data Mining Conference: AusDM 2008, Stamford Grand, Glenelg, Adelaide, 27-28 November 2008
Y. S. Koh (2008). Mining Non-coincidental Rules without a User Defined Support Threshold, in Takashi Washio, Einoshin Suzuki, Kai Ming Ting, Akihiro Inokuchi (Eds.): Advances in Knowledge Discovery and Data Mining, 12th Pacific-Asia Conference, PAKDD 2008, Osaka, Japan, May 20-23, 2008 Proceedings. Lecture Notes in Computer Science, pp. 910-915 (Presented Talk)
Y.S. Koh and R. Pears (2008). Transaction Clustering Using a Seeds Based Approach, in Takashi Washio, Einoshin Suzuki, Kai Ming Ting, Akihiro Inokuchi (Eds.): Advances in Knowledge Discovery and Data Mining, 12th Pacific-Asia Conference, PAKDD 2008, Osaka, Japan, May 20-23, 2008 Proceedings. Lecture Notes in Computer Science, pp. 916-922 (Presented Talk)
Y. S. Koh and R. Pears (2007). Mining Non-Coincidental Negative Association Rules, in M.A. Orgun and J. Thornton (eds.), AI 2007, LNAI 4830, pp. 710-714.
Y. S. Koh, N. Rountree and R. O’Keefe (2006). Mining interesting imperfectly sporadic rules, in W. K. Ng, M. Kitsuregawa, J. Li, K. Chang (Eds.), Advances in Knowledge Discovery and Data Mining, 10th Pacific-Asia Conference, PAKDD 2006, Singapore, April 9-12, 2006, Proceedings, Vol. 3918 of Lecture Notes in Computer Science, Springer, pp. 473-482. (Presented Talk)
Y. S. Koh and N. Rountree (2005). Finding sporadic rules using Apriori-Inverse, in T. B. Ho, D. Cheung and H. Liu (eds), Advances in Knowledge Discovery and Data Mining, 9th Pacific-Asia Conference, PAKDD 2005, Hanoi, Vietnam, May 18-20, 2005, Proceedings, Vol. 3518 of Lecture Notes in Computer Science, Springer, pp. 97-106. (Presented Talk)
Y.S. Koh and S.H. Ow (2004). Mobile Phone Usage Growth Rate Indicator (MPID) Based on an Econometric Model, in, Proceedings of the Winter International Symposium on Information And Communication Technology, Cancun, Mexico, 5-8 January 2004, pp. 446-451.
Y.S. Koh and S.H. Ow (2003). Growth Rate of Mobile Phone Usage in Malaysia, Proceedings of the Public Institutions of Higher Learning (IPTA) Research & Development Exposition and Conference 2003, Kuala Lumpur, 2-5 October 2003.

 

Refereed Journal Articles
Y. S. Koh, (2008) Finding Sporadic Rules in the Diagnosis of the Erythemato-Squamous Diseases. Journal of Intelligent Data Analysis 12(6)
Y. S. Koh, N. Rountree and R. O’Keefe (2008). Mining Interesting Imperfectly Sporadic Rules. Knowledge and Information System, 14(2): 179-196
Y. S. Koh, N. Rountree and R. O’Keefe (2006). Finding Non-Coincidental Sporadic Rules using Apriori-Inverse, International Journal of Data Warehousing and Mining 2(2): 38-54.

Book Chapters
Y. S. Koh, and R. Pears (2008). A Multi Methodological Approach to Rare Association Rule Mining, in Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection, IGI Global (Accepted: 20 October 2008)
Y. S. Koh, R. O’Keefe, and N. Rountree (2008). Finding Non-Coincidental Sporadic Rules Using Apriori-Inverse, in  J Wang (Ed), Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications (6 Vol.), Information Science Reference, IGI Global, pp. 3222 -3233
Y. S. Koh,  R. O’Keefe, and N. Rountree (2007). Interestingness Measures in Association Rule Mining, in D. Taniar (Ed.),  Advances in Data Warehousing and Mining (Vol 2), IGI Global, pp. 36 -58

 

Books Edited
Y.S. Koh and N Rountree (2009) Book editor for Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection part of the Advances in Data Warehousing and Mining (ADWM) Book Series (In publication)

 

 

TEACHING

Programming 1

Protocol Analysis and Design

Operating System and Concurrent Programming

Internet Techology

Machine Learning

 

 

PROFESSIONAL SERVICES

2008       Program Committee for Australasian Data Mining (AusDM) Conference
2008       Program Committee for CISIS-2009 International Conference
2008       International Reviewing Member (Malaysian Journal of Computer Science)
2008       Local Arrangement Chair for the Australasian AI Conference in Auckland
2007       Reviewing Member for the 2nd International Conference on Informatics 2007