Research literature clustering using diffusion maps
Abstract
We apply the knowledge discovery process to the mapping of current topics in a particular field of science. We are interested in how articles form clusters and what are the contents of the found clusters. A framework involving web scraping, keyword extraction, dimensionality reduction and clustering using the diffusion map algorithm is presented. We use publicly available information about articles in high-impact journals. The method should be of use to practitioners or scientists who want to overview recent research in a field of science. As a case study, we map the topics in data mining literature in the year 2011.
Main Authors
Format
Articles
Research article
Published
2013
Series
Subjects
Publication in research information system
Publisher
Elsevier
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-201309202329Use this for linking
Review status
Peer reviewed
ISSN
1751-1577
DOI
https://doi.org/10.1016/j.joi.2013.08.004
Language
English
Published in
Journal of Informetrics
Citation
- Nieminen, P., Pölönen, I., & Sipola, T. (2013). Research literature clustering using diffusion maps. Journal of Informetrics, 7(4), 874-886. https://doi.org/10.1016/j.joi.2013.08.004
License
CopyrightCopyright © 2013 Elsevier B.V. This is a final draft version of an article whose final and definitive version has been published in 'Journal of Informetrics' by Elsevier.