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Chatbot - Coggle Diagram
Chatbot
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Advantages
Personable Bots Can Respond, Even When You are Sleeping
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Agent
Customers reach out to chatbot agent to acquire certain information. Hence, the Dialogflow agent needs to be built to handle the conversation.
If the agent accurately identifies the user's intent, it is almost a success!
Intent
An intent categorises the customer's intention for a conversation turn. You can define mutiple intents for a single agent, just like how a call centre agent can decide if you need basic troubleshooting, make an appointment, or redirect your phone calls based on what you say.
What a customer types to the chatbot is referred to as an "end-user expression". Dialogflow matches the end-user expression to the best intent in your agent. Matching an intent is also known as intent classification.
Entity
When an intent is matched, Dialogflow can extract specific information from the end-user expression. The extracted data is called a parameter or entity type. Parameters and entity types are structured data that can help us make better sense of what the user is trying to find out.
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How Dialogflow Works
A Dialogflow conversation begins from the (1) end-user expression, have (2) its intent matched by the agent with the use of training phrases and entities, before (3) response is being provided back to the user.
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