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Unanswerable Question Correction and Explanation over Personal Knowledge Base

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationCIKM 2022 - Proceedings of the 31st ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages4645-4649
Number of pages5
ISBN (Electronic)9781450392365
DOIs
StatePublished - 17 Oct 2022
Event31st ACM International Conference on Information and Knowledge Management, CIKM 2022 - Atlanta, United States
Duration: 17 Oct 202221 Oct 2022

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings
ISSN (Print)2155-0751

Conference

Conference31st ACM International Conference on Information and Knowledge Management, CIKM 2022
Country/TerritoryUnited States
CityAtlanta
Period17/10/2221/10/22

Keywords

  • explainability
  • personal knowledge base question answering
  • unanswerable question

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