Temporal Pattern Classification and Analysis of Large Volume of Data Using Associated Data Placement Algorithm and Online Community Adjustment

Abstract

Aim:The main motto of the study is to optimize the large volume of data using data placement algorithm and online community adjustment algorithm and comparing their accuracy. Materials and Methods: Data placement algorithm (N=10) and online community adjustment (N=10) was iterated 20 times to optimize the data. Result and Discussion: Data placement algorithm has significantly better accuracy (85%) compared to online community adjustment algorithm(78%). The statistical significance of data placement (p<0.02 independent sample test) is high. Conclusion: With the limits of the study, a data placement algorithm with product manufacturing data offers the best accuracy in data optimization.