A Graph-based Methodology for Tracking Covid-19 in Time Series Datasets
| Autor: | Zakariyaa Ait El Mouden, Moha Hajar, Abdeslam Jakimi, Rachida Moulay Taj |
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| Rok vydání: | 2020 |
| Předmět: |
Structure (mathematical logic)
020203 distributed computing 02 engineering and technology computer.software_genre 01 natural sciences Spectral clustering Field (computer science) Data modeling Set (abstract data type) 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Graph (abstract data type) Data mining Time series Cluster analysis 010301 acoustics computer |
| Zdroj: | 2020 IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS) ICECOCS |
| DOI: | 10.1109/icecocs50124.2020.9314516 |
| Popis: | Since its first appearance in December 2019, Covid-19 has become a wide field of scientific research. Starting from biology to bioinformatic solutions, Artificial Intelligence has contributed in turn as a powerful tool for tracking and predicting the outbreak of Covid-19 using different types of datasets. Chest X-ray images are widely used in computer vision applications and Time series datasets are used for predicting the spread of the novel coronavirus. Graph analytics is a recent field of study that links the mathematical definition and operations of a graph to its application in computer science as a complex data structure, this combination has played a critical role in making graph-based applications present in different fields. One of the most powerful graph analytics is community detection which is an intelligent and unsupervised grouping of a set of graph structured data using the similarity between them. The aim of this work is to highlight the importance of graph-based algorithms in tracking Covid-19 using time series datasets, our work will also focus on Spectral Clustering (SC) as a community detection approach to extract clusters from the input datasets. Further applications are needed in order to validate the proposed theoretical approach. |
| Databáze: | OpenAIRE |
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