Some Basic Terms Of Chatbots

ChatBots can be described as an AI software that has the ability to understand and communicate in Human Language through various platforms like web and mobile applications.

Branches of Conversational UI -

Conversational User Interface: It is an interface that allows interaction with users in a more personalized way i.e, it mimics human conversation.

Voice User Interface : It is an interface that allows interaction with users through speech or voice-based commands. Amazon Alexa, Echo Dot, Google Home, Google Mini, Siri, Cortana, and the Google Assistant are the examples of VUI devices which take voice /speech as an input and returns in the same manner.

Types Of Chatbot -

Mainly, chatbots are classified into three types: Rule-Based, AI-Based and Hybrid.

1. Rule Based Chatbot: It is also known as Decision treebots. It has a set of predefined responses from a database for a particular query based on the keywords uttered in the query. So it can be tedious to extract a very lengthy and informative response from the bot. It is just like a decision tree. It gives a response based on the keywords extracted from the user's utterance. Most of them don't use NLP/NLU. The advantage of using this type of is that it is economic.
2. AI Based Chatbot: They are built using ML, NLP/NLU. It also provides answers from a given database but the thing that makes it unique is that it becomes more intelligent over time with the help of past interactions with the users.
3. Hybrid Chatbot: These are the most common type of chatbot. It is basically a mix of both Rule-based and AI-based chatbots. They interact with humans and provide a personalized reply i.e It can start the conversation with the user but when the conversation gets deeper chatbot can be replaced by a human being.

Intent, Entity, And Utterance -

Intent: An intent represents the purpose of a user's input. i.e What is the speaker is trying to do?

Entity: An entity represents a term or object that is relevant to your intents and that provides a specific context for intent or it can be referred to like the things that the speaker is referring to.

Utterance: A Utterance is a branching conversation flow that defines responses to the defined intents and entities. In IBM Watson instead of the word Utterance we use the dialog.

Applications of Chatbots

Chatbots are used across many industries to simplify tasks, save time, and improve user experience. Here are some common areas where they’re making a big impact:

• Customer Service: Chatbots serve the purpose of providing immediate answers to general inquiries and monitoring purchase deliveries and resolving basic customer problems. Websites implement chatbots to extend user greetings and deliver frequently asked questions assistance through automation instead of live human intervention.
• E-commerce: Online retail platforms utilize chatbots to present product suggestions, validate stock availability and help customers complete their purchase transactions. H&M’s automated chat service enables customers to discover clothing selections that match their style preferences.
• Healthcare: Bots help users schedule appointments, issue medication alerts, and answer basic medical questions. WHO uses a chatbot to distribute information about COVID-19.
• Education: Students receive assistance through chatbots which help them select courses, practice quizzes and receive academic support. Language learners can use Duolingo’s chatbot to simulate real-life discussions in multiple languages.
• Banking and Finance: Banks use bots for balance checks, transaction history, and quick customer support. For example, HDFC Bank’s “Eva” helps users with banking services and FAQs.

Natural Language Processing (NLP) in Chatbots

NLP is the technology that allows chatbots to understand and respond to human language naturally. It helps chatbots break down what a person is saying and figure out the best way to reply. Here are the basics:

• Tokenization: This means splitting a sentence into smaller parts (like words or phrases) so the chatbot can understand the structure of what's being said. For example, “Book a ticket to Delhi” becomes ["Book", "a", "ticket", "to", "Delhi"].
• Sentiment Analysis: This helps the bot detect emotions behind the text—whether the user is happy, angry, or confused. It helps the bot respond more politely or escalate to a human when needed.
• Language Modeling: This is how the bot predicts what comes next in a sentence or what the user might mean. It helps chatbots hold more natural conversations and understand different ways of saying the same thing.

Thanks to NLP, chatbots can go beyond basic keyword matching and understand real meaning, tone, and intent—just like a human would in a conversation.

Popular Chatbot Platforms and Tools

There are several tools available to build chatbots, each with its strengths. Here are some of the most popular ones:

• Dialogflow - Great for building chatbots with voice and text support. It’s user-friendly and works well for small to medium businesses. Ideal for customer service bots, especially when integrated with Google Assistant.
• IBM Watson Assistant - Known for its strong AI and NLP features. It’s suitable for enterprises that need more control and customization. Often used in industries like banking and healthcare.
• Microsoft Bot Framework - Best for developers who want to create advanced bots with full control. Works well with Microsoft tools like Azure and Teams. Suitable for complex enterprise-grade bots.
• Rasa (Open Source) - Perfect for developers who want privacy, flexibility, and control. It’s open-source, which means you can host it yourself and customize deeply. Great for companies concerned about data security.
• ChatGPT API (by OpenAI) - Ideal for conversational bots that require human-like responses. It’s powerful for chatbots used in customer service, content generation, or educational tools. Easy to integrate via API.

Conclusion

Online business interactions have experienced fundamental changes through the integration of chatbots which deliver quicker and smarter communication between organizations and their digital users. AI together with Natural Language Processing enables chatbots to interpret human language and generate helpful responses while progressively enhancing their performance. Through platforms such as Dialogflow, Rasa, and ChatGPT API, chatbot development and deployment processes have become more user-friendly. Chatbots now perform everyday tasks more efficiently for the general public across shopping, learning, banking and support services.