Natural language processing

An online workshop talking about some natural language processing concepts and integrating these concepts with designing a chatbot using dialog flow and connecting this chatbot with Facebook.

Dialog flow (formerly called API.AI) is Google-owned chatbot development framework. It is used for Natural Language Processing using machine learning.

Natural Language Processing is a branch of artificial intelligence that deals with analyzing, understanding, and generating the languages that humans use naturally in order to interface with computers in both written and spoken contexts using natural human languages instead of computer languages.

we will talk about the contents of Dialog flow, the definition of each of them, and their use in designing a Chatbot.

Agent: Agents can be described as the app that we create on Dialog flow which holds definition of intents, entities, knowledge base, fulfillment etc. We can export the agent’s zip file.

Intent: What the user wants to do is called an intent, i.e. intention of the user.  Intent is what user wants to do, and not what we do with that information or how we reply. Intents contains many things like contexts, events, training phrases, responses etc.

Entities: For completing a task, we might need some data from the user. For example, for flight booking we need source, destination, date etc. These are called entities.

Chatbot: It is a Google Cloud tool, (Google Cloud  is an initiative by Google to provide cloud computing services to customers). Powered by artificial intelligence that can answer questions automatically. This tool helps to create a smart chatbot (to respond to inquiries from people and customers) that is, to design interactive conversations, the main purpose is to engage customers and collect valuable information.

After that We will talk about natural language processing (to make a chatbot to respond to customers from the following steps).

• Create an agent + name it + and set the language and region (it is for conversational programming).
• Prepare Intents, each one contains the expected questions and answers, and all intents contain the entities and set system options.
• Learn about prebuilt agents that enables us to create a chatbot that predicts questions and answers for each customer based on previous agents or data set.
• The importance of the Chatbot in online shopping for customers, it will show the expected questions + the help of prebuilt agents ready.
• When entering the agent, the requirements (intents + entities) appear. Through this, we customize the expected questions and answers, and we can create a new intent.
  • Then we’ll talk
• Knowledge base, that is, downloading a ready-made knowledge base (text\HTML) to activate it from the settings menu, and set Enable beta features and APl’s to contain a ready-made experience.
• To fetch information from any site and test it on Messenger, with copying the link when creating a new rule

Finally

• We will clarify how to use fulfillment when creating conversations and linking them to Web and Facebook by adding response and setting the location
• and small talk to allocate short questions
• Documentations About Dialog flow.