An Unsupervised Dialogue Topic Segmentation Model Based on Utterance Rewriting

This study proposes a novel unsupervised dialogue topic segmentation method that combines Utterance Rewriting (UR) technique with an unsupervised learning algorithm to efficiently utilize the useful cues in unlabeled dialogues by rewriting the dialogues in order to recover the co-referents and omitted words.