Bibliometric Survey On Clustering Algorithm Of Machine Learning And Its Application

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Bibliometric Survey On Clustering Algorithm Of

Machine Learning And Its Application

Abstract : Machine learning is an application of artificial intelligence. It is an emerging field of computer science. It provides the ability to automatically learn from experience. Learning means to acquire knowledge based on previous experience and perception. Learning can be performed in a supervised or an unsupervised way. Clustering is a type of learning technique that works in an unsupervised way. The objective of this bibliomertic study is to understand the utility of clustering algorithm and machine learning. In this study the author has retrieved 97 research papers from Scopus database which were published from 2003 to 2020. The survey revealed the maximum publication from journals and conferences that associated to computer science.

Index Terms : Artificial intelligence, Bibliometric Analysis, clustering algorithm, deep learning, Machine learning, supervised learning, unsupervised learning.

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1.

INTRODUCTION

Machine learning mainly focuses on new data and changes in the development of computer program. Machine learning algorithm analyses the pattern matching data and predicts the future analysis on the basis of it (R. Ahuja 2020) Machine learning is classified into different categories like supervised, unsupervised and deep learning. Classification and regression are two main types of supervised learning. Supervised learning is performed under the guidance. The new system which develops after sufficient training helps predict the output.

Clustering comes under unsupervised learning.

Unsupervised learning is the techniques that classifies and analysis the data with no labeling. It can be divided into groups based on similarity of data. There are many clustering algorithms available to find clusters that can be used in machine learning, artificial intelligence, data mining and data science.

 Speech recognition

 Face detection

 Spam detection

 Credit Card fraud detection

 Medical diagnosis

Deep learning is a new technology in artificial neural network in the recent year; it comes up as a powerful tool of machine learning for the future of artificial intelligence (Ravì, D., 2016). It plays an important role in the field of speech recognition, image recognition, prediction of drug molecules, predicting the effect of DNA and natural language and analysis of sentiment analysis. To know more about the clustering algorithm and machine learning implementation, there is a need of bibliometric survey in this topic. This paper presents a bibliometric survey from section 2 that highlights the preliminary data collection about clustering and machine learning publication; section 3 shows bibliometric analysis. Section 4 shows the conclusion and reference at the end.

2.

PRELIMINARY

DATA

COLLECTION

The systematic method defines the process to retrieve the primary data collection by search string of documents and final selection of publication from different libraries or databases. There are various databases available like

 Scopus

 Web of science

 Google scholar,

 Research gate

 Clarivate

In this paper author has used Scopus database to search for peer reviewed research literature.

2.1 Search strategy by Keywords

Papers were retrieved by search string with the help of Boolean connector like AND, OR. The paper is based on clustering algorithm and machine learning so the search string is

("Clustering algorithm" AND ‖machine learning" AND

"Unsupervised learning" AND "Artificial Intelligence" OR "deep learning")

2.2 Search strategy for Data

On the basis of primary selection by keywords author received ————————————————

 Rashmi Y. Lad is currently pursuing Ph.D in Computer Studies in Symbiosis International University, Pune, India. E-mail:

[email protected] working in MIT ACSC, Alandi (D),Pune

 Dr. P. S. Metkewar is Professor& Dy. Director at Symbiosis Institute of Computer Studies and Research (SICSR), Symbiosis International (Deemed) University, Lavale , Pune, India e-mail: dy.director @sicsr.ac.in

Fig. 1. Types of Machine Learning

97 papers from 4 different languages from Scopus databases.

Author retrieved 97 papers from the time span of 2003 to 2020 from different journal, conference and book publication from Scopus databases.

2.3 Search strategy by publishing year

In this section author has discussed the publication details year wise and has shown the research paper count of each year in the form of a table. Fig. 3 is a graphical representation of the same.

3.

BIBLIOMETRIC

ANALYSIS

The survey paper has bibliometric analysis performed in two ways.

 Geographical region analysis

 Analysis by keyword, area and affiliation

3.1 Geographical regional analysis

Fig. 4 gives the details of geographical representation of publication of research paper with the help of imapbuilder online tool. This tool takes the data in excel format and then plots the publication country on map.

It is observed in Fig 5 that the highest research work done in clustering and machine learning algorithm is done in India followed by US and china. Lowest research work is done in Germany, Brazil & Australia. Figure shows the publication work country wise.

2673 3.2 Analysis by Keywords

In this bibliometric survey study Fig 6 gives the details of keywords from the research publication retrieved by author. Clustering algorithm and artificial intelligence are the two keywords mostly used in maximum research paper.

3.3. Analysis by Area

Fig. 7 shows the details of subject area in which clustering and machine learning algorithm works. Maximum research publication has been carried out in the subject of computer science i.e. 53% and 20% research work is done in the fields of engineering. Less research work is done in the fields of neuroscience and agricultural and biological science in which still there is a scope of future research.

3.4 Analysis by Affiliation

In this survey paper Fig 8 shows the details of affiliation of top ten universities and their contribution in clustering and machine learning algorithm.

3.5 Analysis details by Affiliation

In this bibliometric survey author has retrieved 97 papers from journal, conference and book chapter. It has been observed that 76.09% of papers were published in conferences, 22.9% of the papers were published in journals and only 1.09% of papers were published in books as a chapter. No contributions from review articles were found.

3.6 Analysis by citation

Author has used PlumX matrix tool for showing the citation details of the research paper ―Subspace learning for unsupervised feature selection via matrix factorization ―. It includes citation details, its usage, abstract and bibliographic information.

CITATIONS

C

Machine learning is an emerging field in the area of computer science. It works in various fields like speech recognition, medical science, finance, prediction and self-driving car etc. This bibliometric study gives a detailed analysis about the topic. The bibliometric survey study on clustering algorithm of machine learning and its application shows maximum publication from LNCS (Lecture notes of Computer Science including Artificial Intelligence and Bioinformatics) category. Most of the research papers from journal, conference and book chapter are affiliated to computer science. The survey revealed that maximum research papers were published in India followed by the US and China.

5.

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