Open Access

ARTICLE

Main Path Analysis to Filter Unbiased Literature

by Muhammad Umair¹, Fiaz Majeed¹, Muhammad Shoaib², Muhammad Qaiser Saleem³, Mohmmed S. Adrees³, Abdelrahman Elsharif Karrar⁴, Shahzada Khurram⁵, Muhammad Shafiq^6,*, Jin-Ghoo Choi⁶

1 Department of Information Technology, University of Gujrat, Gujrat, 50700, Pakistan
2 Department of Computer Science, University of Engineering and Technology, Lahore, Pakistan
3 College of Computer Science and Information Technology, Al Baha University, Al Baha, Saudi Arabia
4 College of Computer Science and Engineering, Taibah University, Al-Madinah, Al-Munawarah, Saudi Arabia
5 Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur, 63100, Pakistan
6 Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, 38541, Korea

* Corresponding Author: Muhammad Shafiq. Email:

(This article belongs to the Special Issue: New Trends in Artificial Intelligence and Deep learning for Instrumentation, Sensors, and Robotics)

Intelligent Automation & Soft Computing 2022, 32(2), 1179-1194. https://doi.org/10.32604/iasc.2022.018952

Received 26 March 2021; Accepted 27 April 2021; Issue published 17 November 2021

Abstract

Citations are references used by researchers to recognize the contributions of researchers in their articles. Citations can be used to discover hidden patterns in the research domain, and can also be used to perform various analyses in data mining. Citation analysis is a quantitative method to identify knowledge dissemination and influence papers in any research area. Citation analysis involves multiple techniques. One of the most commonly used techniques is Main Path Analysis (MPA). According to the specific use of MPA, it has evolved into various variants. Currently, MPA is carried out in different domains, but deep learning in the field of remote sensing has not yet been considered. In this paper, we have used three centrality attributes which are Degree, Betweenness and Closeness centrality to automatically identify important papers by applying clustering method based on machine learning (i.e., K-means). In addition, the main path is drawn from important papers and compared with existing manual methods. In order to conduct experiments, a data set from Web of Science (WOS) has been established, which contains 538 papers in the field of deep learning. Compared with existing works, our method provides the most relevant papers on the main path.

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Keywords

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