• DocumentCode
    3337036
  • Title

    Definition and Extraction of Causal Relations for QA on Fault Diagnosis of Devices

  • Author

    Lee, Sheen-Mok ; Shin, Ji-Ae

  • Author_Institution
    Comput. Sci. Dept., Korea Adv. Sci. & Technol., Daejeon
  • Volume
    2
  • fYear
    2008
  • fDate
    3-5 Nov. 2008
  • Firstpage
    82
  • Lastpage
    85
  • Abstract
    Causal relations in ontology should be defined based on the inference types necessary to solve the tasks specific to application, as well as domain. In this paper, we present a model to define and to extract causal relations for application ontology, which is targeted, as a case study, to serve a question-answering (QA) system on fault-diagnosis of electronic devices. In the first phase, causal categories are defined by identifying the generic inference patterns of QA on fault-diagnosis. In the second, the semantic relations between concepts in the corpus denoting the causal categories are defined as causal relations. In the third, instances of causal relations are extracted using the lexical patterns from the definitional statements of terms in domain, and extended with information from thesaurus. On the evaluation by domain experts, our model shows precision of 92.3% in classifying relations at the definition phase and precision of 80.7% in identifying causal relations at the extraction phase.
  • Keywords
    electronic engineering computing; fault diagnosis; inference mechanisms; ontologies (artificial intelligence); causal relation extraction; electronic device fault-diagnosis; generic inference patterns; lexical patterns; ontology; question-answering system; Application software; Artificial intelligence; Auditory displays; Cause effect analysis; Computer science; Data mining; Driver circuits; Fault diagnosis; Ontologies; Thesauri; application ontology; causal inference; causal relation; diagnostic QA; relation definition; relation extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 2008. ICTAI '08. 20th IEEE International Conference on
  • Conference_Location
    Dayton, OH
  • ISSN
    1082-3409
  • Print_ISBN
    978-0-7695-3440-4
  • Type

    conf

  • DOI
    10.1109/ICTAI.2008.137
  • Filename
    4669759