Unanswerable Question Correction and Explanation over Personal Knowledge Base

An Zi Yen, Hen Hsen Huang, Hsin Hsi Chen

研究成果: Conference contribution同行評審

摘要

Handling unanswerable questions in knowledge base question answering (KBQA) has been a focus in recent years. However, how to explain why a given question is unanswerable is rarely discussed. In this work, we seek not only to correct unanswerable questions based on a personal knowledge base, but also to explain the reason of the correction. We argue that different types of questions need heterogeneous subgraphs with different types of connections. We thus propose a heterogeneous subgraph aggregation network with a two-level attention mechanism to detect important entities and relations in subgraphs and attend to informative subgraphs for different questions. We conduct comprehensive experiments on five subgraphs and their combinations, with results that attest the effectiveness of incorporating heterogeneous subgraphs.

原文English
主出版物標題CIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management
發行者Association for Computing Machinery
頁面4645-4649
頁數5
ISBN(電子)9781450392365
DOIs
出版狀態Published - 17 10月 2022
事件31st ACM International Conference on Information and Knowledge Management, CIKM 2022 - Atlanta, United States
持續時間: 17 10月 202221 10月 2022

出版系列

名字International Conference on Information and Knowledge Management, Proceedings

Conference

Conference31st ACM International Conference on Information and Knowledge Management, CIKM 2022
國家/地區United States
城市Atlanta
期間17/10/2221/10/22

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