Download CSE 8331 FALL 2003 DATA MINING

CSE 8331 SPRING 2010
ADVANCED TOPICS IN DATA MINING
Updated 2/16/10
Professor Margaret H. Dunham
800U Expressway Towers
phone:(214) 768-3087
fax: (214) 768-3085
[email protected]
http://lyle.smu.edu/~mhd
Class: 11-12:20 TTh ; 205 Junkins
Office Hours: 9:00-10:45 TTh (in SIC)
Text:
Data Mining Introductory and Advanced Topics, by Margaret H. Dunham, Prentice-Hall, 2003
(Recommended but not required).
Course Description:
This is a second course in Data Mining targeting the development of research skills. A
prerequisite is successful completion of CSE 7331 or other Introductory Data Mining course.
Please contact Dr. Dunham if you have concerns or questions about this prerequisite. It is
assumed that every student is familiar with the basic data mining topics (clustering, classification,
and association rules) and has some experience with one or more data mining tools (XLMiner,
Weka, etc.).
Due to the fact that there are off campus students, the inclass structure will be primarily lecture but students are encouraged to ask questions and participate.
All material submitted by students is to be their own work. Plagiarism will not be tolerated.
All students are expected to be familiar with and follow the SMU honor code policy:
http://www.smu.edu/studentlife/PCL_05_HC.asp
ANY STUDENT FOUND PLAGIARIZING WILL RECEIVE AN AUTOMATIC GRADE OF 0
ON THAT ASSIGNMENT. A SECOND INSTANCE OF CHEATING BY THAT STUDENT
WILL RESULT IN A GRADE OF F FOR THE COURSE.
NO EXTENSIONS will be automatically given to due dates for distance students.
Grading:
Project I – Presentation
Project II – Survey Paper
Project III – Original paper
CSE 8331, Spring 2010
30%
30%
40%
1
As this is a research class, each student is expected to submit three projects. There will be no
tests or homework.
The three projects are:
 Project I consists of each student individually preparing a 20-25 minute presentation
providing an overview of one published research article.
 Project II requires that each student individually prepare a survey paper on a data mining
topic of his/her choice.
 Project III requires that students divide into groups of size 2-3, perform individual
research, and submit an original paper suitable for publication.
Performing independent research requires that students be able to read and understand related
research papers, provide effective presentations on research, and be able to write summaries of
related work. In addition, since data mining is a very applied Computer Science area, researchers
must be able to set up, perform, and analyze experiments. The projects are aimed at giving
students experience in these areas. Most data mining research requires collaboration. The final
project is aimed at providing experience in performing collaborative work and actually submitting
a paper suitable for publication. You will only submit it to me. However, it is hoped that some
of these will lead to real submissions later on.
Initially three topics are planned to be covered in this class. However, if any students really want
to cover other material, this can be done. Each of the topics to be covered will consist of three
basic sections in class: introduction/overview material, literature, and student presentations.
Approximately three-four students will give presentations in each area. Topics and dates of
presentations are on a first-come-first-served basis.
Tentative Schedule (Updated 2/16/10):
Introduction/Projects/EMM
Stream Mining
Text Mining
Bioinformatics Mining
Additional Student Presentations
CSE 8331, Spring 2010
1/19 – 1/21
Introduction
1/26 – 2/4
Stream Mining Readings
2/9 – 2/18
Stream Mining Student Presentations
2/23 – 2/25
Introduction
3/2 – 3/4
Text Mining Readings
3/16 – 3/23
Text Mining Student Presentations
3/25
SPRING BREAK 3/9 – 3/11
Project II Due 3/30 Midnight
Introduction
3/30 – 4/8
Bioinformaticws Mining Readings
4/13 – 4/20
Bioinformatics Mining Student
4/22
Presentations
4/27 – 4/29
Project III Due 5/6 Midnight
2