Memorias de investigación
Ponencias en congresos:
Optimizing Automated Term Extraction for Terminological Saturation Measurement
Año:2019

Áreas de investigación
  • Ciencias de la computación y tecnología informática

Datos
Descripción
Assessing the completeness of a document collection, within a domain of interest, is a complicated task that requires substantial effort. Even if an automated technique is used, for example, terminology saturation measurement based on automated term extraction, run times grow quite quickly with the size of the input text. In this paper, we address this issue and propose an optimized approach based on partitioning the collection of documents in disjoint constituents and computing the required term candidate ranks (using the c-value method) independently with subsequent merge of the partial bags of extracted terms. It is proven in the paper that such an approach is formally correct ? the total c-values can be represented as the sums of the partial c-values. The approach is also validated experimentally and yields encouraging results in terms of the decrease of the necessary run time and straightforward parallelization without any loss in quality.
Internacional
Si
Nombre congreso
15th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer
Tipo de participación
960
Lugar del congreso
Kherson, Ucrania
Revisores
Si
ISBN o ISSN
1613-0073
DOI
Fecha inicio congreso
12/06/2019
Fecha fin congreso
15/06/2019
Desde la página
1
Hasta la página
16
Título de las actas
Proceedings of the 15th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume I: Main Conference

Esta actividad pertenece a memorias de investigación

Participantes
  • Autor: Victoria Kosa Department of Computer Science, Zaporizhzhia National University
  • Autor: David Chaves Fraga UPM
  • Autor: Hennadii Dobrovolskyi Department of Computer Science, Zaporizhzhia National University
  • Autor: Egor Fedorenko Department of Computer Science, Zaporizhzhia National University
  • Autor: Vadim Ermolayev Department of Computer Science, Zaporizhzhia National University

Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial