Abstract:Collaborative Communication platforms (e.g., Slack) support multi-party conversations which contain a large number of messages on shared channels. Multiple conversations intermingle within these messages. The task of conversation disentanglement is to cluster these intermingled messages into conversations. Existing approaches are trained using loss functions that optimize only local decisions, i.e. predicting reply-to links for each message and thereby creating clusters of conversations. In this work, we propo… Show more
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