Webinar - Building a ChatBot using IBM Watson Conversation Service

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Conversational ChatBot using IBM Watson Conversation Service

■ Leveraging the power of Artificial Intelligence, Chatbots are essentially virtual robots that are transforming the way companies interact and engage with their customers.

■ Chatbots are rapidly gaining user traction and being used across domains and use cases. They are getting up-close and personal to their human counterparts, to a point at which its sometimes difficult to tell the difference!

■ Using Chatbots, businesses are now able to engage consumers in more ways than ever before:

1. Content Consumption 2. Customer Service3. Transactional Engagements

Transforms Business Models

Business Applications

Use Cases

■ Order/Transactions Management

■ Customer Support■ Technical Support ■ Concierge Services■ Financial Consulting ■ Virtual Assistant

Sectors

■ Retail ■ Telecom & ISP■ Banking & Financial ■ Medical Services

How Chatbots WorkChatbots are created for a specific purpose.

■ Rule Based: Function on pre-defined set of options and answers questions which are within its designed parameters.

■ Artificial Intelligence Based: Function on more sophisticated Data Sciences related techniques like:- Natural Language Processing- Sentiment Analysis and - Deep Learning

Steps to creating successful Chatbots1. Identify the problem to be solved and understand the

use cases

2. Choose the channel for your Bot, Facebook Messenger, Skype, Slack, etc.

3. Choose the service you will use to build your Chatbot:Azure Bot Service, IBM Watson, Motion.ai, etc.

4. Emulate conversations and train Chatbot accordingly.

5. Test

6. Launch

LIVE DEMO

Tools for creating Chatbots

By using

IBM Watson Conversation

NoSQL DB

Prerequisite

1. An IBM Bluemix account to create Watson Conversation Service.

2. A Cloud Foundry application to host the frontend application.

3. A Python Flask application to act as API.

Setup Watson Conversation1. Intents2. Entities3. Dialog

An Intent is a purpose or goal expressed in a customer's input, such as answering a question or processing a bill payment. By recognizing the intent expressed in a customer's input, the Conversation service can choose the correct dialog flow for responding to it.

An Entity represents a class of object or a data type that is relevant to a user's purpose. By recognizing the entities that are mentioned in the user's input, the Conversation service can choose the specific actions to take to fulfill an intent.

The Dialog component of the Conversation service uses the intents and entities that are identified in the user's input, plus context from the application, to interact with the user and ultimately provide a useful response. Your dialog is represented graphically as a tree; create a branch to process each intent that you define.

What is Context?The dialog context is the mechanism for passing information between the dialog and your application code.

Sample Context:

{"context": {"my_dessert_string": "ice-cream","toppings_array": ["onion", "olives"],"age_number": 18,"complex_object": {"user_firstname" : "Peter","user_lastname" : "Pan","has_card" : false

}}

}

SCREENSHOTS

Demo – Front Screen 1

Demo – Front Screen 2

Bluemix Login Screen

Select Watson Conversation Service

Create Watson Conversation Service

Create WorkSpace

Define Intents

Define Entities

Create Dialog Tree

Information Sources1. Watson Conversation Documentation: https://tinyurl.com/lny9eha2. Python Flask CF App SDK for Bluemix: https://tinyurl.com/m8hqvvo3. Python SDK for Watson Developer Cloud: https://tinyurl.com/lkuanmy

Disclaimer:

There are several SDKs are available for Watson and Bluemix services. We have just used Python SDK for our Demo purpose. The same application can be developed using other languages.

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