IntentDial: An Intent Graph based Multi-Turn Dialogue System with Reasoning Path Visualization

• URL: http://arxiv.org/abs/2310.11818v1
• Date: Wed, 18 Oct 2023 09:21:37 GMT
• Title: IntentDial: An Intent Graph based Multi-Turn Dialogue System with Reasoning Path Visualization
• Authors: Zengguang Hao and Jie Zhang and Binxia Xu and Yafang Wang and Gerard de Melo and Xiaolong Li
• Abstract summary: We present a novel graph-based multi-turn dialogue system called. It identifies a user's intent by identifying intent elements and a standard query from a graph using reinforcement learning.
• Score: 24.888848712778664
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Intent detection and identification from multi-turn dialogue has become a widely explored technique in conversational agents, for example, voice assistants and intelligent customer services. The conventional approaches typically cast the intent mining process as a classification task. Although neural classifiers have proven adept at such classification tasks, the issue of neural network models often impedes their practical deployment in real-world settings. We present a novel graph-based multi-turn dialogue system called , which identifies a user's intent by identifying intent elements and a standard query from a dynamically constructed and extensible intent graph using reinforcement learning. In addition, we provide visualization components to monitor the immediate reasoning path for each turn of a dialogue, which greatly facilitates further improvement of the system.

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