NLP Applications: Chatbots, Sentiment Analysis, and Beyond
NLP Applications: Chatbots, Sentiment Analysis, and Beyond Natural Language Processing (NLP) helps machines interpret human language. In this post we explore three practical areas: chatbots that converse with people, sentiment analysis that reads opinions, and other useful tasks that sit behind the scenes. The goal is to explain simply what you can build, what to watch for, and how to get started with reasonable effort. Chatbots rely on three core ideas: intent recognition, entity extraction, and dialogue management. The system tries to identify what the user wants, pull out important details (like dates or names), and decide what to say next. A clear example is a restaurant assistant: a user asks for a 7 pm table, the bot confirms party size, checks availability, and books the slot. Good bots keep context across turns, ask for missing details, and offer easy fallbacks when they are unsure. Common challenges include ambiguous language, changing goals, and jargon. Simple rules work for routine tasks, while neural models handle varied language better but need monitoring. ...