A machine-learning scraping tool for data fusion in the analysis of sentiments about pandemics for supporting business decisions with human-centric AI explanations

The COVID-19 pandemic is changing daily routines for many citizens with a high impact on the economy in some sectors. Small-medium enterprises of some sectors need to be aware of both the pandemic evolution and the corresponding sentiments of customers in order to figure out which are the best commercialization techniques. This article proposes an expert system based on the combination of machine learning and sentiment analysis in order to support business decisions with data fusion through web scraping. The system uses human-centric artificial intelligence for automatically generating explanations. The expert system feeds from online content from different sources using a scraping module. It allows users to interact with the expert system providing feedback, and the system uses this feedback to improve its recommendations with supervised learning. © 2021. Kumar et al. All Rights Reserved.

Авторы
Kumar S.A.1 , Nasralla M.M.2 , García-Magariño I.3, 4 , Kumar H. 5
Журнал
Издательство
PeerJ Inc.
Язык
Английский
Страницы
1-18
Статус
Опубликовано
Том
7
Год
2021
Организации
  • 1 IIIT AllahabadUttar Pradesh, India
  • 2 Department of Communications and Networks Engineering, Prince Sultan University, Riyadh, Saudi Arabia
  • 3 Universidad Complutense de Madrid, Madrid, Spain
  • 4 Instituto de Tecnología del Conocimiento, UCM, Madrid, Spain
  • 5 Peoples ' Friendship University of Russia, Moscow, Russian Federation
Ключевые слова
Business intelligence; COVID-19; Data Mining and Machine Learning; Decision support system; Machine learning; Natural Language and Speech; Network Science and Online Social Networks; Pandemics; Sentiment analysis
Дата создания
16.12.2021
Дата изменения
16.12.2021
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/76944/
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Orazov M.R., Radzinsky V.E., Orekhov R.E.
Гинекология. Общество с ограниченной ответственностью Медицинское маркетинговое агентство МедиаМедика. Том 23. 2021. С. 314-323