Automated case creation and management for diagnostic CBR systems

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TypeArticle
ConferenceApplied Intelligence: The International Journal of Artificial Intelligence, Neural Networks and Complex Problem-SolvingTechnologies, February 2008.
VolumeVolume 28, Number 1
Subjectcase-based reasoning; case bases; automated case creation; methodology; natural language processing
AbstractWith the rapid development of case-based reasoning (CBR) techniques such as case retrieval and case adaptation, CBR has been widely applied to various real-world applications. A successful case-based reasoning system requires a high-quality case base, which provides rich and efficient solutions for solving real-world problems. How to automatically create and manage such a case base is a vital but unsolved problem. This paper tackles this important problem. We proposed a methodology for creating cases from readily available large-sized databases, which were collected in the routine operations. Building on techniques from case-based reasoning and natural language processing, we present a methodology for automatically creating cases at the initial stage of a CBR system development. After the detailed description of the methodology, we introduce a case study for validating the usefulness of the methodology. The experimental results show that the proposed methodology significantly reduces the human effort required for authoring cases, and we are able to automatically create the high-quality cases for diagnostic CBR systems from historic maintenance and operational data at the initial stage of system development.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number48817
NPARC number8913839
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Record identifier45b2a303-d843-475b-a2f2-c0bd7a84fe0b
Record created2009-04-22
Record modified2016-05-09
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