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一种用于大流行情绪分析中数据融合的机器学习抓取工具，通过以人类为中心的人工智能解释来支持商业决策。

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

作者信息

Kumar Swarn Avinash, Nasralla Moustafa M, García-Magariño Iván, Kumar Harsh

机构信息

IIIT Allahabad, Uttar Pradesh, India.

Department of Communications and Networks Engineering, Prince Sultan University, Riyadh, Saudi Arabia.

出版信息

PeerJ Comput Sci. 2021 Sep 17;7:e713. doi: 10.7717/peerj-cs.713. eCollection 2021.

DOI:10.7717/peerj-cs.713
PMID:34616891
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8459777/
Abstract

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.

摘要

新冠疫情正在改变许多公民的日常生活，对某些行业的经济产生重大影响。某些行业的中小企业需要了解疫情的发展情况以及客户的相应情绪，以便找出最佳的商业化技术。本文提出了一种基于机器学习和情感分析相结合的专家系统，通过网络爬虫进行数据融合，以支持商业决策。该系统使用以人为本的人工智能自动生成解释。专家系统通过一个爬虫模块从不同来源的在线内容中获取信息。它允许用户与专家系统进行交互并提供反馈，系统利用这些反馈通过监督学习来改进其建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4cc/8459777/d0c6ef56a91c/peerj-cs-07-713-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4cc/8459777/d0c6ef56a91c/peerj-cs-07-713-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4cc/8459777/a03787d1c0db/peerj-cs-07-713-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4cc/8459777/081288f2d6db/peerj-cs-07-713-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4cc/8459777/d17d9bcf6e56/peerj-cs-07-713-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d4cc/8459777/894268da434c/peerj-cs-07-713-g004.jpg
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Customer Centricity in Medical Affairs Needs Human-centric Artificial Intelligence.医学事务中的以客户为中心需要以人为本的人工智能。
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Sentiment analysis and its applications in fighting COVID-19 and infectious diseases: A systematic review.
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Analysis of COVID-19 clinical trials: A data-driven, ontology-based, and natural language processing approach.基于数据驱动、本体和自然语言处理技术的 COVID-19 临床试验分析。
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