id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-301405-7ijaxk4v	El Mouden, Zakariyaa Ait	Towards Using Graph Analytics for Tracking Covid-19	2020-12-31		.txt	text/plain	3763	181	55	The purpose of this paper is to introduce a graph-based approach of communities detection in the novel coronavirus Covid-19 countries' datasets. Recent works combined between spectral methods and deep learning models, such as the case of [24] where the authors presented their deep clustering approach to cluster data using both neural networks and graph analytics. Our proposed approach consists of a SC based communities detection where the objective is to have an unsupervised grouping of countries having similar behaviors of Covid-19 spreading. In this paper, we proposed a graph-based approach for clustering Covid-19 data using spectral clustering. Ongoing work intends to link the different processes of the model, developed with two different programming languages (Java and R) to build a model able to cluster heterogeneous data based on graph analytics and spectral clustering for communities' detection. An application of spectral clustering approach to detect communities in data modeled by graphs	./cache/cord-301405-7ijaxk4v.txt	./txt/cord-301405-7ijaxk4v.txt