Scientific Production on GPS Trajectory Clustering: A Bibliometric Analysis

dc.contributor.authorGary Reyes
dc.contributor.authorRoberto Tolozano-Benites
dc.contributor.authorLaura Cristina Lanzarini
dc.contributor.authorCésar Armando Estrebou
dc.contributor.authorAurelio F. Bariviera
dc.coverage.spatialBolivia
dc.date.accessioned2026-03-24T15:00:34Z
dc.date.available2026-03-24T15:00:34Z
dc.date.issued2025
dc.description.abstractClustering 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.
dc.identifier.doi10.3390/ijgi14040165
dc.identifier.urihttps://doi.org/10.3390/ijgi14040165
dc.identifier.urihttps://andeanlibrary.org/handle/123456789/100668
dc.language.isoen
dc.relation.ispartofISPRS International Journal of Geo-Information
dc.sourceUniversity of Guayaquil
dc.subjectGlobal Positioning System
dc.subjectTrajectory
dc.subjectCluster analysis
dc.subjectComputer science
dc.subjectData science
dc.subjectGeodesy
dc.subjectGeography
dc.subjectArtificial intelligence
dc.subjectPhysics
dc.titleScientific Production on GPS Trajectory Clustering: A Bibliometric Analysis
dc.typearticle

Files