A criteria based function for reconstructing low-sampling trajectories as a tool for analytics

Abstract: Mobile applications equipped with Global Positioning Systems have generated a huge quantity of location data with sampling uncertainty that must be handled and analyzed. Those location data can be ordered in time to represent trajectories of moving objects. The data warehouse approach base...

Full description

Autores:
Ospina Álvarez, Edison Camilo
Tipo de recurso:
Fecha de publicación:
2015
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/53687
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/53687
http://bdigital.unal.edu.co/48310/
Palabra clave:
0 Generalidades / Computer science, information and general works
62 Ingeniería y operaciones afines / Engineering
Personalized routing
Graph theory - Data processing
Imputation process
Data compression (telecomunication)
Low sampling trajectories
Criteria based trajectory reconstruction
Global Positioning Systems
Information analysis
Sistema global para comunicaciones móviles
Teoría de grafos - Procesamiento de datos
Compresión de datos (Telecomunicación)
Análisis de información
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:Abstract: Mobile applications equipped with Global Positioning Systems have generated a huge quantity of location data with sampling uncertainty that must be handled and analyzed. Those location data can be ordered in time to represent trajectories of moving objects. The data warehouse approach based on spatio-temporal data can help on this task. For this reason, we address the problem of personalized reconstruction of low-sampling trajectories based on criteria over a graph for including criteria of movement as a dimension in a trajectory data warehouse solution to carry out analytical tasks over moving objects and the environment where they move