Virtual Assistants
Kore.ai Platform
Key Concepts
Natural Language Processing (NLP)
Accessing Platform
Virtual Assistant Builder
Virtual Assistant Types
Getting Started
Creating a Simple Bot
Dialog Task
Dialog Builder (New)
Dialog Builder (Legacy)
User Intent Node
Dialog Node
Entity Node
Supported Entity Types
Composite Entities
Supported Colors
Supported Company Names
Form Node
Logic Node
Message Nodes
Confirmation Nodes
Bot Action Node
Service Node
Custom Authentication
2-way SSL for Service nodes
Script Node
Agent Transfer Node
WebHook Node
Grouping Nodes
Connections & Transitions
Manage Dialogs
User Prompts
Knowledge Graph
Importing and Exporting
Knowledge Extraction
Alert Tasks
Ignore Words and Field Memory
How to Schedule a Smart Alert
Small Talk
Digital Views
Configuring Digital Views
Digital Forms
How to Configure Digital Forms
Machine Learning
Model Validation
Fundamental Meaning
NLP Guidelines
Knowledge Graph
How to Use Traits
Ranking and Resolver
Advanced NLP Configurations
Context Management
Session and Context Variables
Context Object
How to Manage Context Switching
Manage Interruptions
Dialog Management
Sub-Intents & Follow-up Intents
Amend Entity
Multi-Intent Detection
Sentiment Management
Tone Analysis
Sentiment Management
Event Based Bot Actions
Default Conversations
Default Standard Responses
Talk to Bot
Utterance Testing
Batch Testing
Record Conversations
Custom Dashboard
How to Create Custom Dashboard
Conversation Flows
NLP Metrics
Universal Bots
Enabling Languages
Smart Bots
koreUtil Libraries
Language Management
PII Settings
IVR Integration
General Settings
Import & Export
Collaborative Development
Plan Management
API Overview
API List
API Collection
SDK Overview
SDK Security
SDK App Registration
Web SDK Tutorial
Message Formatting and Templates
Mobile SDK Push Notification
Widget SDK Tutorial
Widget SDK – Message Formatting and Templates
Web Socket Connect & RTM
Using the BotKit SDK
BotKit SDK Tutorial – Agent Transfer
BotKit SDK Tutorial – Flight Search Sample Bot
Using an External NLP Engine
Creating a Simple Bot
Creating a Banking Bot
Context Switching
Using Traits
Schedule a Smart Alert
Configure UI Forms
Add Form Data into Data Tables
Configuring Digital Views
Add Data to Data Tables
Update Data in Data Tables
Custom Dashboard
Custom Tags to filter Bot Metrics
Patterns for Intents & Entities
Build Knowledge Graph
Global Variables
Content Variables
Using Bot Functions
Configure Agent Transfer
Update Balance Task
Transfer Funds Task
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  3. Virtual Assistants
  4. Overview
  5. Chatbot Overview

Chatbot Overview

Communication has been the essence of life from the beginning of times. With the evolution of technology, mode, and style of communication have also evolved.

In the early days, conversations were restricted to verbal and textual interaction between humans. These interactions are usually guided by emotions, context, and awareness of the previous conversation. With the advent of computers, interactions have now expanded to include machines i.e. human-machine interactions. The transition from a command-based interface to a Graphical User Interface (GUI) to a Conversational User Interface (CUI) was natural, need-based and this transition made the communication easier.

With CUI, came chatbots that interact with users in a natural language. Further enhancements using Artificial Intelligence and NLP capabilities enabled a chatbot to understand user utterance in the natural language; derive the task from the user utterance as well as extract the information required to successfully execute the task.

AI-driven, NLP-based chatbots and voice assistants are the latest in technology and a must for all businesses these days.

What are Conversational Bots?

A Conversational Bot or Chatbot is a virtual assistant that acts as an intelligent intermediary between people, digital systems, and internet-enabled things. It replaces the traditional Graphical User Interfaces (GUIs) of an application or website with a Conversational User Interface. It is a paradigm shift from the earlier communications achieved either by entering syntax-specific commands or clicking icons.

Chatbots are designed to chat with users through a combination of natural language-based conversations. Responses come in the form of buttons, calendars, or other widgets that accelerate the speed with which a user can respond.

AI-powered messaging solutions or Conversational Bots serves as the stepping stone to the future. A Conversational Bot is an automated computer program skilled in digital media communication. It communicates through intelligent virtual agents, organizations’ apps and websites, social media platforms, and messenger platforms. Users can interact with such bots using voice or text to access information, complete tasks, and execute transactions.

So what makes the Conversational Bot so special? This in a nutshell:

What are Intents & Entities?

A Conversational Bot faces three challenges:

  1. Intent Detection – Understanding what the user wants.
  2. Entity Extraction – Extracting the required information from the user to accomplish what the user wants.
  3. Dialog Flow/Conversation – Accomplishing the user wants.

Whatever the user says is considered as an Utterance. It is the task of the Conversational Bot to extract from this user utterance, the intent, and entities essential to carry a conversation. For example, let us consider the following user utterance: I want to fly to London this weekend.

An Intent is the user’s intention. It usually comes in the form of a verb or noun within the user utterance. From the above user utterance, a Conversational Bot understands the user intent as want to fly and triggers the corresponding dialog task.

Entities are a collection of data or information that the Bot requires to complete the task as identified in the user intent. There can be multiple entities in various formats that are required by the Bot. These can be a part of user utterance or the Bot needs to prompt the user for the entity values. For example, in the above user utterance, London, and this weekend form the values for the entities Destination and Travel Date respectively. As you can notice, the Source entity value is missing and the Bot needs to prompt the user for the same.

As seen, an Entity can be of any type like location, date, time, person, etc,.

How to Build Intelligent Bots?

Bots are not smart by default. They are made capable of showing some level of artificial intelligence by leveraging technologies like machine learning, big data, natural language processing, etc. A chatbot is intelligent when it is aware of user needs, understands the user’s perspective or context, and responds according to the user’s mood or emotion. Its intelligence gives the chatbot the ability to handle any scenario of a conversation with ease.

The key for a Conversational Bot to understand humans is; its ability to identify the human intentions, extract relevant information from the user utterance and map the relevant action/task against that utterance. NLP (Natural Language Processing) is the science of extracting the intention (Intent) of text and relevant information (Entity) from the text.

Managing dialogs to keep track of multiple conversation threads, remembering the context, and responding to the user tone or sentiment provides the much-needed humane touch to the conversation and at the same time serving the user with accurate and appropriate responses.

Another aspect that helps build an intelligent Bot is having a Knowledge Base. This gives the Bot an ability to respond to frequently asked questions that return static responses. Building Knowledge Collection is an attempt to represent entities, ideas, and events with all their interdependent properties and relations according to a system of categories. This structured categorization of data helps the Bot to answer user queries effectively and with ease.