Cargando…
Spatiotemporal Filtering Pipeline for Efficient Social Networks Data Processing Algorithms
One of the areas that gathers momentum is the investigation of location-based social networks (LBSNs) because the understanding of citizens’ behavior on various scales can help to improve quality of living, enhance urban management, and advance the development of smart cities. But it is widely known...
Autores principales: | Mukhina, Ksenia, Visheratin, Alexander, Nasonov, Denis |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7304753/ http://dx.doi.org/10.1007/978-3-030-50433-5_7 |
Ejemplares similares
-
Orienteering Problem with Functional Profits for multi-source dynamic path construction
por: Mukhina, Ksenia D., et al.
Publicado: (2019) -
Pixelated Carrier Phase-Shifting Shearography Using Spatiotemporal Low-Pass Filtering Algorithm
por: Yan, Peizheng, et al.
Publicado: (2019) -
Data analysis and modeling pipelines for controlled networked social science experiments
por: Cedeno-Mieles, Vanessa, et al.
Publicado: (2020) -
pyAmpli: an amplicon-based variant filter pipeline for targeted resequencing data
por: Beyens, Matthias, et al.
Publicado: (2017) -
ngsComposer: an automated pipeline for empirically based NGS data quality filtering
por: Kuster, Ryan D, et al.
Publicado: (2021)