Process / pipeline

Intent Detection — Intent Classification

Intent detection is a natural-language-understanding task that classifies the purpose behind a user utterance — such as making a reservation, asking for information, or filing a complaint — into one of a set of predefined intent classes. It is a core NLU component of conversational interfaces and customer-service automation systems, drawing on the benchmarks of Larson et al. (2019) and Casanueva et al. (2020).

Open in MethodMindSoonVideoSoon

Read the full method

Members only

Sign in with a free account to read this section.

Sign in

Sources

  1. Larson, S. et al. (2019). An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction. EMNLP. DOI: 10.18653/v1/D19-1131
  2. Casanueva, I. et al. (2020). Efficient Intent Detection with Dual Sentence Encoders. ACL Workshop on NLP for Conversational AI. DOI: 10.18653/v1/2020.nlp4convai-1.5

Related methods

Referenced by

ScholarGateIntent Detection (Intent Detection (Intent Classification)). Retrieved 2026-06-04 from https://scholargate.app/en/text-mining/intent-detection