@inproceedings{b31cc75ede9f4a17aa7345a5f9b3f22a,
title = "COVID-19 on the Time, Countries Deaths Monitoring and Comparison Dealing with the Pandemic",
abstract = "This paper aims to implement time series normalization methods in order to compare situations for top countries with more deaths due to COVID-19 over the time. In this work, a dashboard set was created using Power BI for analytical dashboards, is tracked the daily data dynamics of the pandemic which is collected and represented graphically. For all data collecting were developed various web scraping scripts mainly based on bash scripting and python which extract data from specific web sites and once the initial inputs are obtained, the transforming process is started. This includes making aggregations, key performance indicators, correlations and mappings giving the facility to use that transformed data for future works. The data has been collected and treated for study from different sources [1–4]. Additionally, all the results and final data after transformations are being published on a daily basis in the following sites [5–8].",
keywords = "COVID-19, Coronavirus, Daily COVID deaths, SARS-CoV-2, Time series comparison",
author = "Mart{\'i}nez, {Juan J.} and Alexander Gelbukh and Hiram Calvo",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; 20th Mexican International Conference on Artificial Intelligence, MICAI 2021 ; Conference date: 25-10-2021 Through 30-10-2021",
year = "2021",
doi = "10.1007/978-3-030-89817-5_24",
language = "Ingl{\'e}s",
isbn = "9783030898168",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "315--326",
editor = "Ildar Batyrshin and Alexander Gelbukh and Grigori Sidorov",
booktitle = "Advances in Computational Intelligence - 20th Mexican International Conference on Artificial Intelligence, MICAI 2021, Proceedings",
address = "Alemania",
}