The Evolution of Trends and Techniques used for Data Mining

Abstract

Data mining has got the festivity among the most emerging fields of the current epoch. Extensive data is being generated therefore the need of the hour is to mine the interesting trends and patterns. For mining such trends, different techniques and algorithms are introduced and applied during the last decades. In this paper, we are extracting the essence from massive text corpora in the form of potential techniques used in the esteemed field of data mining. For the purpose of exploring the trends, we considered the time span from 2014 to 2018. For this purpose, a novel dataset comprising of the abstracts and metadata of 5,843 articles is procured. All the extracted contents of data mining are published in esteemed journals indexed by ScienceDirect. Text mining techniques including noun phrase mining and TF-IDF are employed to reveal the evolution of hot trends in the field of data mining during the underlying span. For better visualization, the year-wise and overall evolution of these hot trends is presented in the form of the word cloud. Machine learning algorithms are found as the shoulders of the giants, on which, data mining domain is standing.