subject: MCA Project Idea - Data Mining for Student Admission Classification [print this page] MCA Project Idea - Data Mining for Student Admission Classification
This article is one in a series of articles that we will publish on MCA Project Ideas.
Student Admission process is typically a complex process where a number of students are vying for a small number of seats of preference which typically results in a mismatch in terms of seat allocation. Students typically do not get the Branch or specialization that they prefer at the same time colleges typically do land up with seats being unfilled. This is a typical Data Mining problem involving an analysis of trends of student admission process, understanding student demographics and their application patterns and an analysis of seat allocations and unfilled seats. This project will need to be implemented in phases. Typically we need to first start by collecting valid student admission data. This can be possibly done for a single college to start with to analyze the pattern in that college.
Language Recommendations Java .NET
Tool Recommendations Eclipse Visual Studio Weka
Platform Recommendations Windows Linux
Implementation Tips Implementation:
Phase1: Implement a Datawarehouse where this data can be collected for a few years.
Phase2: Basic Analytics of the Data identifying high level patterns
Phase3: Data Mining and Trend Discovery.
Data to be collected:
* Available seats in the college for the year, distributed by branch/specialization,cut off
* Students Applications for the college/branch
* Demographic information of the students
* Seats availability after the completion of the admission process.
Useful References Predictive Data Mining by By Sholom M. Weiss, Nitin Indurkhya
For more details on this project idea and other MCA Project ideas visit Peepaal - Data Mining for Student Admission Classification. This is a forum where you can have useful discussions on projects and ideas with industry professionals.
