#How we Created an Open-Source COVID-19 Chatbot
The coronavirus outbreak has major consequences for society worldwide. People are rightly concerned and have many urgent questions. The World Health Organization provides answers to frequently asked questions regarding the coronavirus on their website (link). However, you may have to search for a while before you have found the right answer to your question. It is vital that people are well informed about current measures. This way we can efficiently limit mass spread. A chatbot could perfectly help with this!
#What is a chatbot?
A chatbot can no longer be called an exceptional luxury in the year 2020. I can say with some certainty that almost everyone, whether consciously or unconsciously, has been in contact with a chatbot. For example, you probably asked questions to digital customer services or other online chat services. During such a conversation, the chatbot knows how to answer your questions, ask questions, or possibly refer you to a website where your questions can be answered. Chatbots are also to be found on websites and instant messenger programs (including Skype, Facebook Messenger, and Slack).
#How does a chatbot work?
Now we know what a chatbot is, what it can be used for and what the benefits are for both the consumer and the producer. But how exactly does a chatbot work and how does a chatbot understand language? We will now go through this step by step, starting with the subject of language understanding.
First : Natural Language Processing (NLP)
Second : Neural Networks
Third : Universal Sentence Encoder (USE)
#In this Chatbot
The project is made up of several independent components. The game of data is gathered in an Excel file. The graphical interface is that presented by the TkinterApp.py. The part relating to the network model of neurons where intelligence resides is contained in the file TrainingSetChatbot.py