An intelligent system for assisting personalized COVID-19 vaccination location selection: Taiwan as an example
Digital Health
; 8:16, 2022.
Article
in English
| Web of Science | ID: covidwho-1916883
ABSTRACT
In many regions of the world, with the gradual increase in the supply of COVID-19 vaccines, COVID-19 vaccination has changed from centralized government control to personalized selection. When choosing a location for COVID-19 vaccination, in addition to subjective preferences, objective information (such as the expected waiting time at a COVID-19 vaccination location and the crowdedness and reliability of the vaccination location) also need to be considered. However, it is not convenient for an individual to collect and compare such information. To address this issue, this research applies web content mining to extract the conditions of COVID-19 vaccination locations. Then, a novel asymmetric calibrated fuzzy inverse of column sum and fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje recommendation mechanism is proposed. Finally, an intelligent system is developed to assist a user in selecting a personalized COVID-19 vaccination location. In a regional experiment conducted in Taichung City, Taiwan, the developed intelligent system was applied to assist 20 users in choosing personalized COVID-19 vaccination locations. The successful recommendation rate was 95%.
Full text:
Available
Collection:
Databases of international organizations
Database:
Web of Science
Topics:
Vaccines
Language:
English
Journal:
Digital Health
Year:
2022
Document Type:
Article
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