Home Page of Ramakrishnan Kannan

This course is being offered by Prof. M. N. Murthy.

The course is expected to cover the meet the following objectives.

1. Clustering
2. Classification
3. Association Rule Mining
4. Incremental Mining
5. Divide and Conquer approach
6. Compressed Data Mining
7. Regression

Most of the topics will be covered through papers and I will be providing the papers that is covered under each of the above topic. I will also make the programming assignments available in this page.

Attached is the .xls sheet of my total course work.

Programming Assignment 1: Clustering using PAM and classification using K-NNC over character recognition data.
Programming Assignment 2: Association Rule Mining generation using FP-Tree over character recognition data.

Mining Project

Collaborative Filtering Recommender Systems using Association Rule Mining
Recommender systems are quite famous in any
business happening in the web. Few classical examples are
Amazon’s recommender system, Netflix movie recommender
systems, Orkut’s community recommender systems etc. As part of
this report we are trying to explore the traditional recommender
systems, current recommender systems, and extend to our model
of exploring FP-Tree for generating association rules. We are also
presenting our experimental analysis and giving the future
directions in this area.
Report  Java Source code and Executables