Por favor, use este identificador para citar o enlazar este ítem: 10.5771/0943-7444-2017-3-139

Título: SISA: Automatic indexing system for scientific articles. Experiments with location heuristics rules versus TF-IDF rules
Fecha de publicación: 2017
Editorial: International Society for Knowledge Organization
Cita bibliográfica: Knowledge Organization, volumen 44(2017), nº 3
ISSN: 0943-7444
Materias relacionadas: CDU::3 - Ciencias sociales
Palabras clave: Automatic indexing
SISA
Scientific articles
Terms
Controlled vocabulary
Information
Resumen: Indexing is contextualized and a brief description is provided of some of the most used automatic indexing systems. We describe SISA, a system which uses location heuristics rules, statistical rules like term frequency (TF) or TF-IDF to obtain automatic or semi-automatic indexing, depending on the user’s preference. The aim of this research is to ascertain which rules (location heuristics rules or TF-IDF rules) provide the best indexing terms. SISA is used to obtain the automatic indexing of 200 scientific articles on fruit growing written in Portuguese. It uses, on the one hand, location heuristics rules founded on the value of certain parts of the articles for indexing such as titles, abstracts, keywords, headings, first paragraph, conclusions and references and, on the other, TF-IDF rules. The indexing is then evaluated to ascertain retrieval performance through recall, precision and f-measure. Automatic indexing of the articles with location heuristics rules provided the best results with the evaluation measures.
Autor/es principal/es: Gil-Leiva, Isidoro
Facultad/Departamentos/Servicios: Facultades, Departamentos, Servicios y Escuelas::Departamentos de la UMU::Información y Documentación
URI: http://hdl.handle.net/10201/136640
DOI: 10.5771/0943-7444-2017-3-139
Tipo de documento: info:eu-repo/semantics/article
Número páginas / Extensión: 25
Derechos: info:eu-repo/semantics/openAccess
Descripción: © 2017. This document is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the Accepted version of a Published Work that appeared in final form in Knowledge Organization. To access the final edited and published work see DOI 10.5771/0943-7444-2017-3-139
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