方法证据记录
Intent Detection
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).
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Intent Detection (Intent Classification)
分类方法记录 · process-pipeline / text-mining
- Larson, S. et al. (2019). An Evaluation Dataset for Intent Classification and Out-of-Scope Prediction. EMNLP. · DOI 10.18653/v1/D19-1131
- 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
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