Method and tool for generating table of relevance in literature review (MTTR)

Ruiz, Natasha, Winter, Rogério, Rosa, Ferrucio de Franco, Shukla, Pancham and Kazemian, Hassan (2021) Method and tool for generating table of relevance in literature review (MTTR). In: ECKM - 22nd European Conference on Knowledge Management, 2-3 September 2021, Virtual. (In Press)

Preview

Text mttr eckm v9 Natasha.pdf - Accepted Version Download (521kB) | Preview

Abstract / Description

Every day, researchers in computing and IT are challenged with several articles that they need to rate, classify and separate quickly and effectively to contextualize and further advance their research effectively. It is considered that literature review is the most important step of discovery. Notably, a literature review is a part that allows the researcher to adjust the perspectives and limitations of an area of study. However, there is a lack of effective methods and tools for this activity. Often, traditional knowledge management techniques result in the “Gordian Knot” slowing down the process of literature review considerably.

In this article, we present a Method and Tool for Generating Table of Relevance in Literature Review (MTTR). The MTTR is an innovative organizing method supported by software tools that make the literature review activity more efficient, faster and cheaper. An interesting feature of MTTR is data visualization using the Heat Map technique, Word Cloud and statistical techniques in designating and comparing each scientific article with the other relevant articles. The productivity gains in MTTR occur due to the automation in structuring and sorting scientific articles. In addition to efficiency, the lowest cost has the potential to place the MTTR as a preferred tool for the researcher. The anecdotal evidence reported in this article suggests that it is possible to carry out a literature review in a much shorter time with MTTR than in the traditional manner.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	The paper will be presented during 2-3 September 2021 and will be published in Proceedings. The published work (e-book and printed book) will be available from Academic Bookshop with following ISBN/ISSN. E-Book ISBN: 978-1-914587-07-8 E-Book ISSN: 2048-8971 Book version ISBN: 978-1-914587-06-1 Book Version ISSN: 2048-8963
Uncontrolled Keywords:	review method; heat map; word cloud; active learning tools; systematic review
Subjects:	000 Computer science, information & general works
Department:	School of Computing and Digital Media
Depositing User:	Panchamkumar Shukla
Date Deposited:	26 Aug 2021 08:31
Last Modified:	03 Sep 2021 01:58
URI:	https://repository.londonmet.ac.uk/id/eprint/6931

Downloads

Actions (login required)

View Item