LUIS For Natural Language Understanding
LUIS or Language Understanding Intelligent Service provides language understanding cognitive intelligence to bots and any other applications. It enables developers to develop smart applications that can understand human language and respond accordingly to your requests. It allows your application to understand what a person wants in their own words. It uses machine learning to allow developers to build applications. These applications can receive your input in natural language and extract meaning from it. Any client application like a dialog system or a chat bot, can pass your input to a LUIS app and receive results tat provide natural language understanding. It is a service developed by Microsoft that has algorithms to understand human language.
A LUIS app or LUIS model is defined by a developer for a specific application or domain. Once the app is published, a client application sends utterances(text in their own words ) to the LUIS end point as an HTTP request. It applies the learned model to the natural language text to provide intelligent understanding about your input. It returns a json formatted response. The client application uses the json response to make decisions about how to fulfill your requests. These decisions can include some decision tree in the bot framework code and calls to other services. A common client application for LUIS is a chat bot.
LUIS app contain a domain specific natural language model. You can start the LUIS app model with a prebuilt domain model or built with your own model. Prebuilt model LUIS has many prebuilt domain models including intents, utterances, and prebuilt entities. These models include the entire design for you and are a great way to start using LUIS quickly. Training is the process of teaching your app by example to improve its language understanding. When you train the app, LUIS generalizes from the examples and learns to recognize the the relevant intents and entities in the future. After you train your app, you test it with sample utterances to see if the intents and entities are recognized correctly. If not, make updates to the app, train and test again. Once you finish building, training, and testing your app, you can publish it.
LUIS brings in AI to applications so that computers and humans can speak with each other seamlessly. It is built on machine learning and complex algorithms.