Usage of Measures of Interestingness in Educational Data

Abstract

With the growing amount of data a new field called data mining is emerging extremely quickly. Data mining tools which perform data analysis may uncover important data patterns, contributing greatly to business strategies, knowledge bases, and scientific, educational and medical research. Association rules mining is one of the most well studied data mining tasks. It discovers relationships among attributes in databases, producing if-then statements concerning attribute-values. There are increasing research interests in using data mining in education. This new emerging field, called Educational Data Mining, concerns with developing methods that discover knowledge from data come from educational environments. This paper shows how data mining can be used to come up with interesting knowledge from student database. We identify the measure of interestingness and implement them on student database and come up with interesting rules that can help teachers and related people to deal with students and understand their behavior and activities.

Authors and Affiliations

Monika Srivastava| Department of Information Technology Technocrat Institute of Technology Bhopal, India Monika_srivastava1@yahoo.com, Sweta Gupta| Department of Information Technology Technocrat Institute of Technology Bhopal, India Swetagupta_it@yahoo.co.in

Keywords

Related Articles

A Web Usage Mining Framework for Business Intelligence

In this paper, we introduce a web mining solution to business intelligence to discover hidden patterns and business strategies from their customer and web data. We propose a new framework based on web mining technology....

Simulation in Wireless Sensor Networks

Simulation tools for wireless sensor networks are increasingly being used to study sensor webs and to test new applications and protocols in this evolving research field. There is always an overriding concern when using...

Analysis and Comparison of TAPSK with Multilevel Coding and Non-Coherent Detection for Different Channel Conditions

Error is one of the most important fields in digital communication system. Since error is unavoidable during communication the error correcting codes are used to overcome this problem. Generally the error correcting code...

Modified Mapping Rules For English To Marathi Translation

Natural Language Processing is the growing area of research. Machine Translation, an integral part of Natural Language Processing, is important for breaking the language barrier and facilitating the inter-lingual communi...

Coin Recognition Using Circular Hough Transform

This paper represents algorithm for recognition of the coins of different denomination. The proposed system first uses a canny edge detection to generate an edge map, then uses CHT (Circular Hough transform) to recognize...

Download PDF file
  • EP ID EP8269
  • DOI -
  • Views 548
  • Downloads 28

How To Cite

Monika Srivastava, Sweta Gupta (2011). Usage of Measures of Interestingness in Educational Data. International Journal of Electronics Communication and Computer Technology, 1(2), 30-35. https://europub.co.uk/articles/-A-8269