Structure Extraction in Task-Oriented Dialogues with Slot Clustering
This is the official code repository for the paper Structure Extraction in Task-Oriented Dialogues with Slot Clustering by Liang Qiu, Chien-Sheng Wu, Wenhao Liu and Caiming Xiong.
Abstract
Extracting structure information from dialogue data can help us better understand user and system behaviors. In task-oriented dialogues, dialogue structure has often been considered as transition graphs among dialogue states. However, annotating dialogue states manually is expensive and time-consuming. In this paper, we propose a simple yet effective approach for structure extraction in task-oriented dialogues. We first detect and cluster possible slot tokens with a pre-trained model to approximate dialogue ontology for a target domain. Then we track the status of each identified token group and derive a state