TITLE:
Findings Seminal Papers Using Data Mining Techniques
AUTHORS:
Alexander Báez Hernández, Debrayan Bravo Hidalgo
KEYWORDS:
Seminals Papers, Knowledge Management, Entrepreneurship, Marketing, Outlier Detection, Data Mining, State of the Art
JOURNAL NAME:
Open Journal of Social Sciences,
Vol.8 No.9,
September
25,
2020
ABSTRACT: The aim of this contribution is to show the detection of seminal papers
using data mining techniques. To achieve the objective of this research,
Rapidminer Studio software and its data mining tools are used, based on data
created with information extracted from Google Scholar and Scopus, in three
different areas of knowledge. In this process, other softwares such
as Microsoft Excel and Publish or Perish are used. Comparing the results
obtained for the searches in Knowledge Management, Entrepreneurship and Marketing, it was
obtained that there is no marked similarity between the sets of articles that
were obtained in Google Scholar and Scopus. The values for the Similarity Index
remained below 0.52%, similar between Knowledge Management and Entrepreneurship
but decreasing for Marketing. The detection of outliers using Data Mining techniques
and in particular using Rapidminer, allowed to determine the seminals papers
for the three search terms analyzed and allowed to characterize these in the
space, in Google Scholar and Scopus. It was shown that the seminal articles can
be different if Google Scholar or Scopus is used. The results suggest determining
for other search terms whether the trend found is maintained or not.