Spring 2007 Data Mining

tealackingAI and Robotics

Nov 8, 2013 (3 years and 10 months ago)

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Spring 2007

Data Mining

Dr. Xiaoyan Li

Department of Computer Science

Mount Holyoke College

email:

xli@MtHolyoke.edu


phone:

(413) 538
-
2554

Course Description

Data Mining has become one of the most exciting and fastest growing fields in computer science.
Data Mining refers to various techniques which can be used to uncover hidden information from
a database. The data to
be mined may be complex
,

multimedia
data including
text, graphics,
video, audio and bioinformatics data
. Data Mining has evolved from several areas including:
databases, artificial intelligence,
machine learning,
pattern recognition,

multimedia
information

retrieval, and
can be applied to the exploration of hidden information from web, video, and
bioinformatics

data
. This course is designed to provide
senior under
graduate students with
introductory

of data mining concepts and tools. In addition, related con
cepts such as
information
retrieval,
web mining

and bioinformatics
will be covered.


Prerequisites:

CS 211

and
CS 221

or permission of instructor

Visible Notes:

2 meetings (75 minutes)

Course Syllabus


Part I. Introduction and Related Topics

1.
Introduction: tasks, issues, metrics and social implications

2.
Related
t
opics

in da
tabase
:

OLTP,

OLAP
and data warehousing

3. Relate
t
opics

in

information retrieval
:

web search,
question
-
answering
and novelty detection

4. Related Topics in
artificial intelligence:
machine learning and pattern matching

Part II. Core Techniques

1.
Classification
:

Bayes
ian, KNN, ID3, ANN, rule
-
based

2.
Clustering
:

hierarchical, partitional, clustering in large database

3.
Associate Rules
:

basic and advanced algorithms

Part III. Advanced Topics

1.
Web
M
ining
:

contents, structure and usage

2.
I
mage/
Video Mining
:

CBIR, MPE
G
-
7, video event detection

3.
Bioinformatics
:

biology preliminaries, information aspects, microarray data clustering

Textb
ook
:


Data Mining Introductory and Advanced Topics by Margaret H. Dunham Prentice Hall, 2003
Book Web Page


References:

Data Mining: Multimedia, Soft Computing, and Bioinformatics, Su
shmita Mitra, Tinku Acharya,
ISBN: 0
-
471
-
46054
-
0, Hardcover, 424 pages, September 2003

http://www.wiley.com/WileyCDA/WileyTitle/productCd
-
0471460540.html


Principle of Data Mining, by Hand, Mannila and Smith, MIT Press, 2001.

http://mitpress.mit
.edu/catalog/item/default.asp?ttype=2&tid=3520