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Case Completion of Workflows for Process-Oriented Case-Based Reasoning

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Case-Based Reasoning Research and Development (ICCBR 2016)

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Abstract

Cases available in real world domains are often incomplete and sometimes lack important information. Using incomplete cases in a CBR system can be harmful, as the lack of information can result in inappropriate similarity computations or incompletely generated adaptation knowledge. Case completion aims to overcome this issue by inferring missing information. This paper presents a novel approach to case completion for process-oriented case-based reasoning (POCBR). In particular, we address the completion of workflow cases by adding missing or incomplete dataflow information. Therefore, we combine automatically learned domain specific completion operators with generic domain-independent default rules. The empirical evaluation demonstrates that the presented completion approach is capable of deriving complete workflows with high quality and a high degree of completeness.

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Notes

  1. 1.

    The terms completeness and consistency used here with respect to workflows must not be confused with the use of those terms within logics — here, we mean something different, as defined below.

  2. 2.

    Within the same control-flow block.

  3. 3.

    We omit the index if it is obvious which ontology is referenced.

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Acknowledgements

This work was funded by the German Research Foundation (DFG), project number BE 1373/3-1.

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Correspondence to Gilbert Müller .

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Müller, G., Bergmann, R. (2016). Case Completion of Workflows for Process-Oriented Case-Based Reasoning. In: Goel, A., Díaz-Agudo, M., Roth-Berghofer, T. (eds) Case-Based Reasoning Research and Development. ICCBR 2016. Lecture Notes in Computer Science(), vol 9969. Springer, Cham. https://doi.org/10.1007/978-3-319-47096-2_20

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  • DOI: https://doi.org/10.1007/978-3-319-47096-2_20

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