A case-based reasoning approach for providing machine diagnosis from service reports

  • Authors:
  • Kerstin Bach;Klaus-Dieter Althoff;Régis Newo;Armin Stahl

  • Affiliations:
  • Competence Center Case-Based Reasoning, German Research Center for Artificial Intelligence (DFKI) GmbH, Kaiserslautern, Germany;Competence Center Case-Based Reasoning, German Research Center for Artificial Intelligence (DFKI) GmbH, Kaiserslautern, Germany;Competence Center Case-Based Reasoning, German Research Center for Artificial Intelligence (DFKI) GmbH, Kaiserslautern, Germany;Competence Center Case-Based Reasoning, German Research Center for Artificial Intelligence (DFKI) GmbH, Kaiserslautern, Germany

  • Venue:
  • ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
  • Year:
  • 2011

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Abstract

This paper presents a case-based reasoning system that has been applied in a machine diagnosis customer support scenario. Complex machine problems are solved by sharing machine engineers' experiences among technicians. Within our approach we made use of existing service reports, extracted machine diagnosis information and created a case base out it that provides solutions faster and more efficient than the traditional approach. The problem solving knowledge base is a data set that has been collected over about five years for quality assurance purposes and we explain how existing data can be used to build a case-based reasoning system by creating a vocabulary, developing similarity measures and populating cases using information extraction techniques.