METHWORK: An Approach for Ranking of Research Trends with a Case Study for IoET

Title:METHWORK: An Approach for Ranking of Research Trends with a Case Study for IoET

Volume: 14 Issue: 4

Author(s): Neeraj Kumar*, Alka Agrawal and Raess A. Khan

Affiliation:

• Department of Information Technology- SIST, BBAU, Central University, Lucknow,India

Keywords: IoT, SLR, dense ranking, Opted Related Keywords (ORK), VANET, METHWORK.

Abstract:

Objective: Ranking in many areas has been a big problem for a long time. The authors tried to use a novel ranking approach to find out the most popular research interest among all the research fields. The authors have assumed that the selection of a research area is a tedious task.

Methods: Therefore, they tried to propose a mechanism named METHWORK (Methodology With the Opted Related Keywords) to choose popular research trends. Google-based searching was applied to find samples in the initial state of this approach. The METHWORK was tested with respect to a case of ranking of research trends within the IoET (Internet of Environmental Things). To find ranks, the first phase is to assess the popularity of the topics in the existing published research papers. To find out the correctness of the ranking found using METHWORK, the authors performed χ2 hypothesis testing while making a comparison with current ranking techniques.

Results: The methodology proposed is a milestone to find out the research trends within a broad research area.

Conclusion: The results of the test indicated that the approach could be applied to determine trends in any research discipline and proved the applicability of the proposed approach.

Cite this article as:

Kumar Neeraj*, Agrawal Alka and Khan A. Raess , METHWORK: An Approach for Ranking of Research Trends with a Case Study for IoET, Recent Advances in Computer Science and Communications 2021; 14 (4) . https://dx.doi.org/10.2174/2213275912666190731122650