Cargando…
Detecting Incremental Frequent Subgraph Patterns in IoT Environments
As graph stream data are continuously generated in Internet of Things (IoT) environments, many studies on the detection and analysis of changes in graphs have been conducted. In this paper, we propose a method that incrementally detects frequent subgraph patterns by using frequent subgraph pattern i...
Autores principales: | Bok, Kyoungsoo, Jeong, Jaeyun, Choi, Dojin, Yoo, Jaesoo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263475/ https://www.ncbi.nlm.nih.gov/pubmed/30453676 http://dx.doi.org/10.3390/s18114020 |
Ejemplares similares
-
Road Speed Prediction Scheme by Analyzing Road Environment Data
por: Lim, Jongtae, et al.
Publicado: (2022) -
User Recommendation for Data Sharing in Social Internet of Things
por: Bok, Kyoungsoo, et al.
Publicado: (2021) -
An Incremental Clustering Algorithm with Pattern Drift Detection for IoT-Enabled Smart Grid System
por: Jiang, Zigui, et al.
Publicado: (2021) -
Complex Event Processing for Sensor Stream Data
por: Bok, Kyoungsoo, et al.
Publicado: (2018) -
The frequent complete subgraphs in the human connectome
por: Fellner, Máté, et al.
Publicado: (2020)