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A case-based reasoning system to recommend solutions for source water protection: knowledge acquisition and modelling

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  • Jérôme Cerutti
  • Irène Abi-Zeid
  • Luc Lamontagne
  • Roxane Lavoie
  • Manuel J. Rodriguez

Abstract

“How can drinking water sources be protected, and how can one learn from others who have faced similar problems?” These questions are becoming increasingly relevant in a context where anthropogenic activities threaten natural resources. We describe in this paper a knowledge acquisition and modelling process to support complex decision-making related to source water protection. We conducted online surveys, interviews and applied thematic analysis to gather and structure knowledge from documented and undocumented sources. Our process resulted in structured descriptions of cases that consist of past problems and their implemented solutions. Case design was based on know-how and knowledge needs expressed by water stakeholders. The case base forms the backbone of a knowledge-based recommender system prototype that implements case-based reasoning. It is meant to guide decision-makers in developing solutions based on past experiences. It is a successful application of knowledge management and sharing of lessons learned for decision-making in practice.

Suggested Citation

  • Jérôme Cerutti & Irène Abi-Zeid & Luc Lamontagne & Roxane Lavoie & Manuel J. Rodriguez, 2022. "A case-based reasoning system to recommend solutions for source water protection: knowledge acquisition and modelling," Knowledge Management Research & Practice, Taylor & Francis Journals, vol. 20(6), pages 828-842, November.
    • Handle: RePEc:taf:tkmrxx:v:20:y:2022:i:6:p:828-842
    DOI: 10.1080/14778238.2022.2075808
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