History Semantic Graph Enhanced Conversational KBQA with Temporal Information Modeling

• URL: http://arxiv.org/abs/2306.06872v1
• Date: Mon, 12 Jun 2023 05:10:58 GMT
• Title: History Semantic Graph Enhanced Conversational KBQA with Temporal Information Modeling
• Authors: Hao Sun, Yang Li, Liwei Deng, Bowen Li, Binyuan Hui, Binhua Li, Yunshi Lan, Yan Zhang, Yongbin Li
• Abstract summary: We propose a History Semantic Graph Enhanced KBQA model (HSGE) that is able to effectively model long-range semantic dependencies in conversation history. We evaluate HSGE on a widely used benchmark dataset for complex sequential question answering.
• Score: 28.27368343751272
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Context information modeling is an important task in conversational KBQA. However, existing methods usually assume the independence of utterances and model them in isolation. In this paper, we propose a History Semantic Graph Enhanced KBQA model (HSGE) that is able to effectively model long-range semantic dependencies in conversation history while maintaining low computational cost. The framework incorporates a context-aware encoder, which employs a dynamic memory decay mechanism and models context at different levels of granularity. We evaluate HSGE on a widely used benchmark dataset for complex sequential question answering. Experimental results demonstrate that it outperforms existing baselines averaged on all question types.

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