Comparing Models for Analysing Database Pattern

Abstract

In today’s scenario, size of database is growing at a tremendous speed and analyzing such data for various purposes is of utmost importance. In this paper, we have applied our methodology to datasets of different sizes and discussed the experiment results in analyzing the pros and cons of various models. We have given an implementation model for knowledge discovery from huge unlabeled temporal databases by employing a combination of HMM and K-means technique.