RT Journal Article
T1 An automatic and association-based procedure for hierarchical publication subject categorization
A1 Urdiales-García, Amalia Cristina
A1 Guzmán-de-los-Riscos, Eduardo Francisco
K1 Publicaciones científicas
K1 Investigación científica - Evaluación
K1 Lingüística computacional
AB Subject categorization of scientific publications, i.e., journals, book series or conference proceedings, has become a main concern in academia, as publication impact and ranking are considered a basic criterion to evaluate paper quality. Publishers usually propose their own categorization, but they often include only their own publications and their categories might not be coherent with other proposals. Also, due to the dynamic nature of science, new categories may frequently appear. As traditional mechanisms for categorization have been questioned by many authors, a new research line has emerged to improve the category assignment process. Approaches usually rely on assessing publication similarity in terms of topics, co-citation, editorial boards, and/or shared author profiles. In this work, we propose a novel procedure for scientific publication hierarchical categorization based on the repetition or absence of relevant descriptors in association rules among publications. The key idea is that publication categories can be automatically defined by strong associations of nuclear topics. Also, some very specific subcategories can be defined by exclusion from any set of rules. This process can be used to construct a data-driven hierarchy of scientific publication categories from scratch or to improve any existing categorization by discovering new fields. In this paper the proposed algorithm uses SJR descriptors all journals in the SCImago dataset and the three-level classification in the Scopus dataset (covering only 35 % of publications of the SCImago dataset) to discover new categories and assign every journal to the resulting enhanced hierarchy one.
PB Elsevier
YR 2023
FD 2023-11-11
LK https://hdl.handle.net/10630/28792
UL https://hdl.handle.net/10630/28792
LA eng
NO Cristina Urdiales, Eduardo Guzmán, An automatic and association-based procedure for hierarchical publication subject categorization, Journal of Informetrics, Volume 18, Issue 1, 2024, 101466, ISSN 1751-1577, https://doi.org/10.1016/j.joi.2023.101466.
NO Funding for open Access charge: Universidad de Málaga / CBUAThis research is partially supported by the Spanish Ministry of Science and Innovation and by the European Regional Development Fund (FEDER), the Junta de Andalucía (JA),and the Universidad de M ́alaga (UMA) through the research projects with reference TED2021-129956B-I00 and UMA20-FEDERJA-065
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 20 ene 2026