Data Mining Application to Attract Students in HEI

TL;DR

This paper explores how data mining techniques, specifically support and confidence measures, can optimize advertising strategies for higher education institutions to attract more students amidst increasing competition.

Contribution

It applies support and confidence data mining methods to identify the most effective advertisement channels for HEIs, addressing resource constraints.

Findings

Support and confidence help identify best advertisement methods

Optimized advertising strategies improve student attraction

Data-driven approach reduces marketing costs

Abstract

In the last two decades, number of Higher Education Institutions (HEI) grows in leaps and bounds. This causes a cut throat competition among these institutions while attracting the student get admission in these institutions. To make reach up to the students institution makes effort of advertisement. Similarly developing and developed both type of institution launch several services also to attract students. Most of the institutions are opened in self finance mode. So all time they feel short hand in expenditure. Now a day a number of advertisement methods are available. So it is difficult for an institution to make advertisement through all modes and launch all services at the same time due to different constraints. In this paper we use support and confidence method to find out the best way of advertisement.