Automatic indexing of scientific articles on Library and Information Science with SISA, KEA and MAUI

Gil-Leiva, Isidoro; Díaz Ortuño, Pedro; Fernandes Correa, Renato

Publication:
Automatic indexing of scientific articles on Library and Information Science with SISA, KEA and MAUI

dc.contributor.author	Gil-Leiva, Isidoro
dc.contributor.author	Díaz Ortuño, Pedro
dc.contributor.author	Fernandes Correa, Renato
dc.contributor.department	Información y Documentación
dc.date.accessioned	2023-12-14T08:47:35Z
dc.date.available	2023-12-14T08:47:35Z
dc.date.issued	2022-10-18
dc.description	© 2022 CSIC. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by /4.0/ This document is the Accepted version of a Published Work that appeared in final form in Revista Española de Documentación Científica. To access the final edited and published work see doi.org/10.3989/redc.2022.4.1917	es
dc.description.abstract	This article evaluates the SISA (Automatic Indexing System), KEA (Keyphrase Extraction Algorithm) and MAUI (Multi-Purpose Automatic Topic Indexing) automatic indexing systems to find out how they perform in relation to human indexing. SISA’s algorithm is based on rules about the position of terms in the different structural components of the document, while the algorithms for KEA and MAUI are based on machine learning and the statistical features of terms. For evaluation purposes, a document collection of 230 scientific articles from the Revista Española de Document ación Científica published by the Consejo Superior de Investigaciones Científicas (CSIC) was used, of which 30 were used for training tasks and were not part of the evaluation test set. The articles were written in Spanish and indexed by human indexers using a controlled vocabulary in the InDICES database, also belonging to the CSIC. The human indexing of these documents constitutes the baseline or golden indexing, against which to evaluate the output of the automatic indexing systems by comparing terms sets using the evaluation metrics of precision, recall, F-measure and consistency. The results show that the SISA system performs best, followed by KEA and MAUI.	es
dc.format	application/pdf	es
dc.format.extent	18	es
dc.identifier.citation	Revista Española de Documentación Científica vOL. 45, Nº 4 e338
dc.identifier.doi	doi.org/10.3989/redc.2022.4.1917
dc.identifier.issn	Print: 0210-0614
dc.identifier.issn	Electronic: 1988-4621
dc.identifier.uri	http://hdl.handle.net/10201/136644
dc.language	eng	es
dc.publisher	Consejo Superior de Investigaciones Científicas	es
dc.relation	Sin financiación externa a la Universidad	es
dc.rights	info:eu-repo/semantics/openAccess	es
dc.rights	Atribución 4.0 Internacional	*
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	*
dc.subject	Automatic indexing	es
dc.subject	Automatic indexing systems	es
dc.subject	SISA	es
dc.subject	KEA	es
dc.subject	MAUI	es
dc.subject	Indexing assessment.	es
dc.subject.other	CDU::3 - Ciencias sociales	es
dc.title	Automatic indexing of scientific articles on Library and Information Science with SISA, KEA and MAUI	es
dc.type	info:eu-repo/semantics/article	es
dspace.entity.type	Publication	es