Scientific Production on GPS Trajectory Clustering: A Bibliometric Analysis

Autores
Reyes, Gary; Tolozano-Benites, Roberto; Lanzarini, Laura Cristina; Estrebou, César Armando; Fernández Bariviera, Aurelio
Año de publicación
2025
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Clustering algorithms or methods for GPS trajectories are in constant evolution due to the interest aroused in part of the scientific community. With the development of clustering algorithms considered traditional, improvements to these algorithms and even unique methods considered as “novel” for science have emerged. This work aimed to analyze the scientific production that exists around the topic “GPS trajectories clustering” by means of bibliometrics. Therefore, a total of 559 articles from the main collection of Scopus were analyzed, initially filtering the generated sample to discard any articles that did not have a direct relationship with the topic to be analyzed. This analysis establishes an ideal environment for other disciplines and researchers since it provides a current state of the trend of the subject of study in their field of research.
Instituto de Investigación en Informática
Materia
Informática
trajectory clustering
GPS trajectories
trajectory clustering algorithms
bibliometrics
bibliometry
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/181644
Acceder
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network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Scientific Production on GPS Trajectory Clustering: A Bibliometric AnalysisReyes, GaryTolozano-Benites, RobertoLanzarini, Laura CristinaEstrebou, César ArmandoFernández Bariviera, AurelioInformáticatrajectory clusteringGPS trajectoriestrajectory clustering algorithmsbibliometricsbibliometryClustering algorithms or methods for GPS trajectories are in constant evolution due to the interest aroused in part of the scientific community. With the development of clustering algorithms considered traditional, improvements to these algorithms and even unique methods considered as “novel” for science have emerged. This work aimed to analyze the scientific production that exists around the topic “GPS trajectories clustering” by means of bibliometrics. Therefore, a total of 559 articles from the main collection of Scopus were analyzed, initially filtering the generated sample to discard any articles that did not have a direct relationship with the topic to be analyzed. This analysis establishes an ideal environment for other disciplines and researchers since it provides a current state of the trend of the subject of study in their field of research.Instituto de Investigación en Informática2025-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/181644enginfo:eu-repo/semantics/altIdentifier/issn/2220-9964,info:eu-repo/semantics/altIdentifier/doi/10.3390/ijgi14040165info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International (CC BY 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:49:37Zoai:sedici.unlp.edu.ar:10915/181644Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:49:37.912SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Scientific Production on GPS Trajectory Clustering: A Bibliometric Analysis
title Scientific Production on GPS Trajectory Clustering: A Bibliometric Analysis
spellingShingle Scientific Production on GPS Trajectory Clustering: A Bibliometric Analysis
Reyes, Gary
Informática
trajectory clustering
GPS trajectories
trajectory clustering algorithms
bibliometrics
bibliometry
title_short Scientific Production on GPS Trajectory Clustering: A Bibliometric Analysis
title_full Scientific Production on GPS Trajectory Clustering: A Bibliometric Analysis
title_fullStr Scientific Production on GPS Trajectory Clustering: A Bibliometric Analysis
title_full_unstemmed Scientific Production on GPS Trajectory Clustering: A Bibliometric Analysis
title_sort Scientific Production on GPS Trajectory Clustering: A Bibliometric Analysis
dc.creator.none.fl_str_mv Reyes, Gary
Tolozano-Benites, Roberto
Lanzarini, Laura Cristina
Estrebou, César Armando
Fernández Bariviera, Aurelio
author Reyes, Gary
author_facet Reyes, Gary
Tolozano-Benites, Roberto
Lanzarini, Laura Cristina
Estrebou, César Armando
Fernández Bariviera, Aurelio
author_role author
author2 Tolozano-Benites, Roberto
Lanzarini, Laura Cristina
Estrebou, César Armando
Fernández Bariviera, Aurelio
author2_role author
author
author
author
dc.subject.none.fl_str_mv Informática
trajectory clustering
GPS trajectories
trajectory clustering algorithms
bibliometrics
bibliometry
topic Informática
trajectory clustering
GPS trajectories
trajectory clustering algorithms
bibliometrics
bibliometry
dc.description.none.fl_txt_mv Clustering algorithms or methods for GPS trajectories are in constant evolution due to the interest aroused in part of the scientific community. With the development of clustering algorithms considered traditional, improvements to these algorithms and even unique methods considered as “novel” for science have emerged. This work aimed to analyze the scientific production that exists around the topic “GPS trajectories clustering” by means of bibliometrics. Therefore, a total of 559 articles from the main collection of Scopus were analyzed, initially filtering the generated sample to discard any articles that did not have a direct relationship with the topic to be analyzed. This analysis establishes an ideal environment for other disciplines and researchers since it provides a current state of the trend of the subject of study in their field of research.
Instituto de Investigación en Informática
description Clustering algorithms or methods for GPS trajectories are in constant evolution due to the interest aroused in part of the scientific community. With the development of clustering algorithms considered traditional, improvements to these algorithms and even unique methods considered as “novel” for science have emerged. This work aimed to analyze the scientific production that exists around the topic “GPS trajectories clustering” by means of bibliometrics. Therefore, a total of 559 articles from the main collection of Scopus were analyzed, initially filtering the generated sample to discard any articles that did not have a direct relationship with the topic to be analyzed. This analysis establishes an ideal environment for other disciplines and researchers since it provides a current state of the trend of the subject of study in their field of research.
publishDate 2025
dc.date.none.fl_str_mv 2025-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/181644
url http://sedici.unlp.edu.ar/handle/10915/181644
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/2220-9964,
info:eu-repo/semantics/altIdentifier/doi/10.3390/ijgi14040165
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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