Automatic Discovery of Novel Intents & Domains from Text Utterances

Understand

One of the primary tasks in Natural Language Understanding (NLU) is to recognize the intents as well as domains of users' spoken and written language utterances.

• Most existing research formulates this as a supervised classification problem with a closed-world assumption, i.e.
• the domains or intents to be identified are pre-defined or known beforehand.
• Real-world applications however increasingly encounter dynamic, rapidly evolving environments with newly emerging intents and domains, about which no information is known during model training.