Natural language processing was developed to help give computers the ability to comprehend conversational language. Through AI, computers are capable of processing human language on a level that understands the intent and sentiment behind queries or searches. NLP is used for digital assistants, GPS, search engines, chatbots, and more.
Put simply, NLP lets computers take human input — whether written or spoken — and process it so a computer can understand. This is done with AI and machine learning, and it allows programs to process large amounts of text swiftly. It can even be done in real-time, like you see when you interact with a chatbot. Natural language processing breaks down texts into smaller units, removes stop words (conjunctions, pronouns, prepositions, etc.), and then reduces words into their root form through stemming and lemmatization. Once preprocessing is complete, a natural language processing algorithm can be developed and used.
Before NLP, it was challenging to process and analyze large amounts of unstructured, text-heavy data. But with NLP, businesses can summarize text, uncover insights and sentiments, run virtual agents, deduce user search intent, and provide relevant responses. This is accomplished through NLP tasks such as speech recognition, parts of speech tagging, named entity recognition, co-reference resolution, word sense disambiguation, natural language generation, and sentiment analysis.
Today's customers want relevant digital experiences. They want intuitive interactions with their devices. Natural language processing helps make that happen, whether through relevant results from natural language search, interactions with AI shopping assistants, or by helping digital assistants better understand spoken words. Businesses are better able to gather advanced insights that were once unattainable, empowering them to offer their customers exceptional experiences. Find out more about how Yext uses modern technology, AI, and NLP in services like Knowledge Graph, Search, and Chat.