 Pattern Recognition and Machine Intelligence Association (PREMIA) is organizing a short course on Introduction to Data Mining, sponsored by SPSS Singapore.
A Short Course on Introduction to Data Mining
Organized by Pattern Recognition and Machine Intelligence Association
Sponsored by SPSS Singapore
14-15 May 2008, School of Computing, Law Link, Singapore 117590
Data mining is a technique that extracts important yet hidden information from vast amounts of data. It has a large number of applications in a variety of different fields. It has been widely used to solve business problems such as customer support, marketing strategy and product development. Data mining also allows researchers to overcome obstacle and discover potential interesting and useful patterns of information embedded in large data sets that will bring insights to their research.
This two-day short course aims to provide a good understanding of the basic algorithms in data mining. This is done by introducing the concepts and techniques of data mining on the first day followed by a series of invited talks on the second day on various practical applications of data mining with a hands-on session.
The first day lecture will cover the following topics:
Data Mining: What is it?
Types of data mining algorithms
Classification techniques
Association rule techniques
Clustering techniques
The following text book, on which the above lecture contents are based, will be provided as part of the course teaching materials.
Data Mining: Concepts and Techniques, (2nd ed.),
by Jiawei Han and Micheline Kamber
Morgan Kaufmann
The second day talks will cover data mining applications in information extraction, fraud detection, bioinformatics, social networking and business problems. An individual hand-on session will also be provided on the second day for each of you to try on your own a user-friendly data mining tool, SPSS Clementine, to practice the basic data mining techniques that you learn on the first day.
At the end of this course, you will be able to
Explain the different data mining techniques
Describe the different types of patterns
Understand the process of data mining
List the strengths / weaknesses of different data mining techniques / algorithms
Appreciate the potentials of data mining techniques for different applications
The following pre-requisites are recommended for the course:
Basic knowledge of data structures and algorithm design
Basic knowledge of linear algebra, probability and statistics and calculus
Registration Fees
Members of PREMIA: S$350.00
Non-members: S$420.00
Student members of PREMIA*: S$150.00
Student non-members*: S$200.00
* Limited seats only for student registration
The registration fee includes course notes, refreshments, the textbook, and a one-year free PREMIA membership subscription, and for non-members, entrance fee to PREMIA membership is waived.
Registration Procedure
The online registration is closed now. If you wish to do manual registration,
please contact Ms Gong Tianxia (gongtian@comp.nus.edu.sg).
After registration, please make your cheque payable to PREMIA and mail it to:
Attn: A/P Tan Chew Lim
School of Computing
National University of Singapore
Computing 1, Law Link
Singapore 117590
If you wish to do online fund transfer, please email PREMIAs treasurer A/P Andrzej Sluzek (ASSLUZEK@ntu.edu.sg) for PREMIA account information.
Registration will close on 30 April 2008. However, due to space limitation and textbook availability, the registration may close before the deadline if the class limit is reached. Please register early to avoid disappointment. If you encounter any problem during registration and if you have any enquiry, please contact Ms Gong Tianxia at GONGTIAN@comp.nus.edu.sg.
PREMIA reserves its right to cancel the course due to circumstances beyond its control.
Course Details:
Day 1: 14 May (Wed) 9.00 am 5.00 pm
Venue: Seminar Room 3A, COM1/212, School of Computing, Law Link, Singapore 117590
Instructor: Assoc. Prof. Wynne Hsu, School of Computing
09.00 10.30: Knowledge Discovery Process
10.30 10.45: Break
10.45 12.00: Classification Algorithms
12.00 13.30: Lunch
13.30 15.00: Association Rules Algorithms
15.00 15.15: Break
15.15 17.00: Clustering Algorithms
Day 2: 15 May (Thu) 9.00 am 5.00 pm
Venue: Programming Lab 1, COM1/B12, School of Computing, Law Link, Singapore 117590
09.00 09.45: Text Data Mining (Dr. Li Xiaoli, I2R)
09.45 10.30: Fraud Data Mining (Dr. Phua Chun Wei, Clifton, I2R)
10.30 10.45: Break
10.45 11.30: Bio Data Mining (Dr. Chua Hon Nian, Kenny, I2R)
11.30 12.15: Network Data Mining (Dr. Ng See Kiong, I2R)
12.15 13.30: Lunch
13.30 15.00: Business Data Mining (Assoc. Prof. Koh Hian Chye, UniSIM)
15.00 15.15: Break
15:15 17.00: Hands-on with SPSS Clementine (Jarrod Teo & Gallen Yip, SPSS)
About the Instructors:
Dr. Wynne Hsu is an Associate Professor at the Department of Computer Science, School of Computing, National University of Singapore (NUS). She received her BSc in Computer Science at National University of Singapore and her M.Sc. and Ph.D in Electrical Engineering from Purdue University, West Lafayette, U.S.A., in 1989 and 1994, respectively. She has published more than 100 technical research papers in various international journals, conference proceedings, and books. She has also served as a program committee member in numerous international conferences including VLDB, ICDE, SIGKDD, PAKDD and DASFAA. Wynne is the principal investigator of a number of government-funded research projects. Her research interests include: knowledge discovery in databases with emphasis on data mining algorithms in relational databases, XML databases, image databases, and spatio-temporal databases.
Dr. Li Xiao-Li is currently a Principal Investigator at the Data Mining Department, Institute for Infocomm Research. He also holds an appointment of adjunct assistant professor in SCE, NTU. Xiao-Li received his Ph.D. degree in Computer Science from Chinese Academy of Sciences in 2001. He was then with NUS (School of Computing/Singapore-MIT Alliance) as a research fellow from 2001 to 2004. His research interests include data mining, machine learning and bioinformatics. He has been serving as the members of technical program committees in numerous machine learning, data mining and bioinformatics related conferences. In 2005, he received best paper award in the 16th International Conference on Genome Informatics (GIW). Please refer to his personal website at http://www1.i2r.a-star.edu.sg/~xlli/ for details.
Dr. Clifton Phua Chun Wei is a Research Fellow at the Data Mining Department of Institute for Infocomm Research (I²R). He has a Doctor of Philosophy and Bachelor of Business Systems (Honours Class I) from Monash University. His current research interests are in security data mining, specifically data leak detection, phishing detection, and plagiarism detection. In addition, he specialises in data mining-based fraud detection, data stream mining, and anomaly detection."
Dr. Kenny Chua Hon Nian obtained his Bachelor in Computer Engineering from the National University of Singapore in 2003. He obtained his Ph.D. degree in Bioinformatics from the National University of Singapore in 2008, under the support of the A*STAR Graduate Scholarship. Hon Nian is currently working as a research engineer at the Data Mining department of the Institute for Infocomm Research, A*STAR. His current research interest is in the application of machine learning and graph-based techniques in biological and medical research.
Dr. Ng See-Kiong (Ph.D., Carnegie Mellon University) is currently the Department Head of the Data Mining Department at Institute for Infocomm Research in Singapore. Prior to returning to Singapore in 2000, See-Kiong did his post-doc in Japan's Keio University studying the effects of in silico cellular simulation. He then moved on to England to work for the pharmaceutical company Smithkline Beecham as their senior investigator in Bioinformatics. After England, See-Kiong moved back to the US to work in a Silicon Valley biotech startup DNA Sciences. See-Kiong's current research focuses on Bioinformatics, Text Mining, Social Network Mining, and Privacy-Preserving Data Mining.
Dr Koh Hian Chye is an Associate Professor and Dean of the School of Business at SIM University (UniSIM). He has published widely in international and regional journals and conferences on topics related to accounting and auditing, business and management, statistical modeling and data mining. His current interest is in the business applications of data mining. Dr Koh frequently acts as a consultant to private companies, large organizations and government agencies. His recent consultancy projects involve data mining applications. He also serves as a trainer in workshops and executive programs. Dr Koh has written a book entitled "Data Mining Applications for Small and Medium Enterprises", which is available at branches of the National Library in Singapore.
The short course is sponsored by SPSS Singapore.
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