RT Journal Article
T1 Improvements for research data repositories: The case of text spam
A1 Vázquez, Ismael
A1 Novo Lourés, María
A1 Pavón Rial, Maria Reyes
A1 Laza Fidalgo, Rosalía
A1 Méndez Reboredo, José Ramón
A1 Ruano Ordás, David Alfonso
K1 1203.17 Informática
AB Current research has evolved in such a way scientists must not only adequately describe the algorithms they introduce and the resultsof their application, but also ensure the possibility of reproducing the results and comparing them with those obtained through otherapproximations. In this context, public data sets (sometimes shared through repositories) are one of the most important elements forthe development of experimental protocols and test benches. This study has analysed a significant number of CS/ML (Computer Science/Machine Learning) research data repositories and data sets and detected some limitations that hamper their utility. Particularly, we identify and discuss the following demanding functionalities for repositories: (1) building customised data sets for specific research tasks, (2)facilitating the comparison of different techniques using dissimilar pre-processing methods, (3) ensuring the availability of software applications to reproduce the pre-processing steps without using the repository functionalities and (4) providing protection mechanisms forlicencing issues and user rights. To show the introduced functionality, we created STRep (Spam Text Repository) web application whichimplements our recommendations adapted to the field of spam text repositories. In addition, we launched an instance of STRep in theURL https://rdata.4spam.group to facilitate understanding of this study
PB Journal of Information Science
SN 01655515
YR 2023
FD 2023-04
LK http://hdl.handle.net/11093/7491
UL http://hdl.handle.net/11093/7491
LA eng
NO Journal of Information Science, 49(2), 285-301 (2023)
NO Xunta de Galicia | Ref. ED431C 2021/44
DS Investigo
RD 19-abr-2025