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Build a Football Chatbot with Oracle Digital Assistant Series by Daniel Teixeira

Juergen Kress
PaaS Partner Adoption

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Thanks for the wonderful blog series to create an ODA chatbot:

Build a Football Chatbot with the Oracle Digital Assistant – Part 1
Build a Football Chatbot with the Oracle Digital Assistant – Part 2 (Backend Integration)
Digital Assistant – Part 3 (Channels)
Updated Backend Integration with Node.js Bot SDK for the Football Chatbot
Build a FAQ Chatbot with Oracle Digital Assistant in 15 minutes

In this post series I will show how to build a Chatbot to provide self-service for football information. You will be able to ask the Bot about results, fixtures, standings and more. The bot will retrieve that information from a backend API service, and it will display the information back to you in one of the many available Channels.

Digital Assistant vs Chatbot

First things first, lets clarify some of the concepts.

A Chatbot is a single purposed program, user initiated, that solves simple business problems by using service automation and self-service.

A Digital Assistant is user oriented. It can assist users with various related or unrelated tasks. Conversations are context aware. Digital assistants can have many different skills, or chatbots, and can route the conversation to/from those skills.

Utterance, Intent and Entity

Utterance: Anything the user says. words or sentences are the utterances.

This is very important as the utterance can significantly vary depending on the user. How many ways one can ask for the game result?

§ “What was the score?”

§ “What’s the result?”

§ “Who won?”

§ “Did they win?”

Intent: An intent is the user’s intention. If the user asks : “Who won the game?” , the intent is the game result. In this case we could call this intent askResults or showResults.

An intent is not the key word the user uses, but rather the high level goal or intention of that sentence.

Entity: An entity can be any field of data that allow to extract important information about the intent. If the user input is: “What is the result from the Real Madrid game yesterday?” -> Yesterday can be a time entity and Real Madrid an entity that defines the who question for the showResults intent.

The Oracle Digital Assistant Natural Language Processing (NLP) engine will be the one responsible to interpret the user text input based on the defined Utterances, Intents and Entities! Read the complete article here.

 

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