Analysis of H-index and Papers Citation in Computer Science Field using K-Means Clustering Algorithm

Abstract

This paper provides an analysis of H-index and paper citations in the computer science field using K-Means Clustering Algorithm. By leveraging cutting edge visual analytics through the use of Power BI and Orange Data Mining tool with K-Means clustering algorithm, we are able to present a comprehensive review of how H-index and citations impact the scholarly evaluation of authors in computer science field. The analysis obtained will assist academics seeking to expand their research influence while providing additional context to the general audience seeking to understand how machine learning algorithms can contribute to data exploration. The analysis conducted has revealed that area of research which has the highest value of citation and H-index include the following topics: Artificial-Intelligence, Computational-Intelligence, Data-mining, Evolutionary-Algorithms, and Big Data Analytics. Finally, the analysis of this research clearly demonstrated that paper citations remain an important factor for determining scientific impact in disciplines such as computer science given its close relationship with established metrics such as h-index scores.

Keywords

• : H-index, Papers Citation, Computer Science, K-means Clustering, Power BI, Analysis