Semi-Supervised Clustering with Contrastive Learning for Discovering New Intents. (arXiv:2201.07604v1 [cs.LG])

Most dialogue systems in real world rely on predefined intents and answers
for QA service, so discovering potential intents from large corpus previously
is really important for building such dialogue services. Considering that most
scenarios have few intents known already and most intents waiting to be
discovered, we focus on semi-supervised text clustering and try to make the
proposed method benefit from labeled samples for better overall clustering
performance. In this paper, we propose Deep Contrastive Semi-supervised
Clustering (DCSC), which …

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