TITLE:
Knowledge Discovery in Learning Management System Using Piecewise Linear Regression
AUTHORS:
S. Mythili, R. Pradeep Kumar, P. Nagabhushan
KEYWORDS:
Histogram, Piecewise Linear Regression, Knowledge Discovery, Big Data, Cluster Analysis
JOURNAL NAME:
Circuits and Systems,
Vol.7 No.11,
September
23,
2016
ABSTRACT: Recent
developments in database technology have seen a wide
variety of data being stored in huge collections. The wide variety makes the
analysis tasks of a generic database a strenuous task in knowledge discovery.
One approach is to summarize large datasets in such a way that the resulting
summary dataset is of manageable size. Histogram has received significant
attention as summarization/representative object for large database.
But, it suffers from computational and space complexity. In this paper, we
propose an idea to transform the histogram object into a Piecewise Linear Regression
(PLR) line object and suggest that PLR objects can be less computational and
storage intensive while compared to those of histograms. On the other hand to carry out a cluster analysis, we
propose a distance measure for computing the distance between the PLR lines.
Case study is presented based on the real data of online education system LMS.
This demonstrates that PLR is a powerful knowledge representative for very large database.