Definition

Words can have different meanings depending on the context. As a human, we learn how these contexts interlink as we grow up and understand how a word can relate to multiple things depending on how it’s placed. Natural Language Classification is a way of teaching a machine to learn a language which is domain-specific, essentially teaching the machine to understand the context in the same way a human would. Meaning they can understand and respond to words depending on their placement or meaning in that structure.

I usually explain this using one of the most popular brand name in the world - Apple. If you take the word Apple on its own you would assume you are referring to the fruit. But, if you are in mobile phone network the word has a different meaning. NLC is used to classify this data with labelling, so when the machine reads the word apple it knows it means a phone type to a phone network, or it could be labelled to mean an apple to a supermarket.

Today leading cloud platforms like IBM and Microsoft offers NLP and NLC offering as a cloud service. For example, IBM Watson Natural Language Classifier service, allows you to train a model to classify text according to classes you define. The Text Analytics API service in Microsoft Azure offers similar features.