DCS 802 Datamining Project


Prof. Sung-Hyuk Cha
Spring 2002
Due: Feb 11th, Mar 8th, Apr 5th, & May 3rd

Description

In this project you will implement a datamining application of your choice using a classfication rule mining such as a decision tree (ID3) or an association rule mining such as apriori algorithm. The project consists of four parts. Each part has a separate due data.
  1. 1st part (due Feb 11th): main goal of your application - you will submit a short proposal of datamining application of your own choice.
  2. 2nd part (due Mar 8th): Input - define the schema for your application and enter sample (at least 100) data.
  3. 3rd part (due Apr 8th): Output and algorithm used - Run the data using either decision tree or apriori algorithm.
  4. 4th part (due May 3rd): The final report on your application.
    1. main goal of your application
    2. input
    3. output
    4. algorithm used
    5. state any extensions you could have done should more time and resources were available.
    be prepared for the presentation slides.
You are allowed to change and to reconsider any previous part based on the review comments and thus the later submission must include all previous parts.

Evaluation

Your document will be reviewed by me and two other students anonymously. After each deadline, you will receive two documents to review.

The review form is here,

  1. Part I Review Form.
  2. Part II Review Form, zipped doc file

Studenttitle
Clara Chang BustBlocker Video Rental
Maheswara P. Kasinadhuni Datamining and Online Analytical Processing for Marketing Sales Problem
Karina Hernandez A Job Search Application using Data Mining Agent
David Ulmer Mining an Online Auctions Data Warehouse
P001Parametric Regression Model in Data Mining
P002Data Mining for the Institute for Community Living
P003Data Mining for Academic Achievements
P005Home Equity Loans Promotion
P006Data mining on Survery data for the student Internet Access
P007Data Mining for the Major League Baseball Players' Hit Performance
P008Data Mining on WWW on-line Purchase via clustering and classification
P009Mining the Data of an Offensive Coordinators Football Play Slections
P011Data Mining for the Outpatient Clinics
P012Datamining for Network Security
P013Improved Web Mining Techniques