Development a Spatial Recommender System for Covid 19 Vaccination Center Based on Fuzzy Method Type II (Study Area: District 6 of Tehran)

Abstract

Covid 19, also known as coronavirus, is an infectious disease caused by the SARS-CoV-2 virus. Anyone can get Covid 19 at any age and become seriously ill or even die. In the meantime, vaccines have saved millions of lives. Covid vaccines are effective for most people 18 years of age and older with autoimmune disorders or underlying diseases. The recommender systems are an intelligent complement to the retrieval of information and refining concepts by analyzing user behaviors and one of the main tools in overcoming the problem of information redundancy. Therefore, in the process of vaccination centers recommending, uncertainty in preferences can be modeled and personalized recommendations can be performed. Therefore, by using the information of users' preferences and properties of vaccination centers based on knowledge-based recommender systems, appropriate arguments can be made about which centers are suitable for users.

Keywords

• covid-19 vaccination center
• recommender system
• fuzzy logic type ii
• user preferences
• som clustring