Operation Diagnosis on Procedure Graph: The Task and Dataset

Ruipu Luo, Qi Zhu, Qin Chen, Siyuan Wang, Zhongyu Wei, Weijian Sun, Shuang Tang

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

3 Scopus citations

Abstract

Users usually consult the manufacturers or the internet when they encounter operation questions with an electronics product. In this paper, we explore to represent an operation question as a procedure graph and formulate the problem of operation diagnosis as two sub-tasks, namely error node detection, and correction, on top of the graph. We construct the first benchmark for this task and propose a transformer-based model to integrate external knowledge and context information to enhance the performance. Experimental results show the effectiveness of our proposed model.

Original languageEnglish
Title of host publicationCIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages3288-3292
Number of pages5
ISBN (Electronic)9781450384469
DOIs
StatePublished - 30 Oct 2021
Event30th ACM International Conference on Information and Knowledge Management, CIKM 2021 - Virtual, Online, Australia
Duration: 1 Nov 20215 Nov 2021

Publication series

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

Conference

Conference30th ACM International Conference on Information and Knowledge Management, CIKM 2021
Country/TerritoryAustralia
CityVirtual, Online
Period1/11/215/11/21

Keywords

  • datasets
  • error detection
  • knowledge graph
  • neural networks

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