Intent Mining from past conversations for conversational agent

1 code implementation • COLING 2020 • Ajay Chatterjee, Shubhashis Sengupta

In this paper, we present an intent discovery framework that involves 4 primary steps: Extraction of textual utterances from a conversation using a pre-trained domain agnostic Dialog Act Classifier (Data Extraction), automatic clustering of similar user utterances (Clustering), manual annotation of clusters with an intent label (Labeling) and propagation of intent labels to the utterances from the previous step, which are not mapped to any cluster (Label Propagation); to generate intent training data from raw conversations.

Clustering Intent Discovery +1