Data Mining

Goals and Objectives:
The aim of the course is to provide the graduate students with an in-depth and hands-on knowledge of algorithms and techniques underlying the field of data mining. The main areas of focus are data mining algorithms, mathematics (linear algebra) and web-scale searching. The course is research oriented and is mainly based on recent literature in the field of data mining. The main focus is providing background information on data mining and further looking at the algorithms from an applied perspective which may involve coding algorithms using efficient data structures, running simulations and comparing results.

Course Outline:

  1. Course Overview & Intro. To Data Mining
  2. Essential Mathematics in Pattern Detection
  3. Classification
  4. ARM
  5. Clustering
  6. Page Rank and Google Wars
  7. LSA/LSI
  8. Cluster based Searching
  9. Other Text Search/Mining Methods
  10. Visual Data Mining
  11. Algorithms for image mining
  12. Fuzzy Logic in Data Mining
  13. Student Presentations
  14. Misc. Topics, Review and Presentations

Text Books:

  • Daniel T. Larose. "Discovering Knowledge in Data: An Introduction to Data Mining." Pub. Wiley-Interscience. 2004.
  • Daniel T. Larose. "Data Mining Methods and Models" Pub. Wiley-IEEE Press 2006.
  • Margaret H. Dunham. "Data Mining: Introductory and Advanced Topics." Prentice Hall; 1st edition 2002
  • David Hand, Heikki Mannila and Padhraic Smyth. “Principles of Data Mining.” Pub. Prentice Hall of India 2004.
  • Sushmita Mitra and Tinku Acharya, “Data Mining: Multimedia, Soft Computing and Bioinformatics.” Pub. Wiley and Sons Inc.2003.
  • Usama M. Fayyad et al, “Advances in Knowledge Discovery and Data Mining.” Pub. The MIT Press, 1996.

Furthermore, a collection of papers addressing specific topics may be distributed in class.

Related Links

Course Name

Location

Introduction

Some introduction from Rutgers university

CS 345 Data Mining

Department of Computer Science, Stanford University

CS 6604: Data Mining

Department of Computer Science At Virginia Tech

Data Mining Methods and Models

From Data Mining Consultants

UCLA Data Mining Lab

Data Mining Lab at UCLA Berkley

Data Mining Resources on the Web

 

The Data Mine Dot COM

Many Resources and Introduction

KDD Cup

Data Mining and Knowledge Discovery Competition