Considering Inter-Case Dependencies During Similarity-Based Retrieval in Process-Oriented Case-Based Reasoning

Autores

  • Rahol Kumar University of Trier
  • Alexander Schultheis University of Trier
  • Lukas Malburg University of Trier & German Research Center for AI (DFKI)
  • Maximilian Hoffmann University of Trier & German Research Center for AI (DFKI)
  • Ralph Bergmann University of Trier & German Research Center for AI (DFKI)

DOI:

https://doi.org/10.32473/flairs.v35i.130680

Resumo

In Case-Based Reasoning (CBR), knowledge gained from previously experienced problem-solving situations is stored as cases that can be used to solve similar upcoming problems. Although these cases act as independent knowledge entities, dependencies between cases are common in real-world scenarios, despite being only rarely considered during case retrieval or other CBR phases. In this paper, we introduce so-called inter-case dependencies, which are considered in the context of Process-Oriented CBR (POCBR). Therefore, we 1) derive requirements that must be satisfied for considering dependencies during the retrieval phase, 2) analyze which knowledge representations are suitable for representing dependencies between cases, and, 3) present our approach for Dependency-Guided Retrieval (DGR) that considers these dependencies between cases during the retrieval phase. In the experimental evaluation, the proposed DGR approach is compared to a regular CBR approach in case retrieval scenarios from the cooking domain. The results demonstrate that the use of the DGR approach leads to significantly reduced times for human problem-solving compared to regular CBR.

Downloads

Publicado

2022-05-04

Como Citar

Kumar, R., Schultheis, A., Malburg, L., Hoffmann, M., & Bergmann, R. (2022). Considering Inter-Case Dependencies During Similarity-Based Retrieval in Process-Oriented Case-Based Reasoning. The International FLAIRS Conference Proceedings, 35. https://doi.org/10.32473/flairs.v35i.130680

Edição

Seção

Main Track Proceedings