Case retrieval in ontology-based CBR systems

Amjad Abou Assali (1) , Dominique Lenne (1) , Bruno Debray (2, 1)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]
2 INERIS - Institut National de l'Environnement Industriel et des Risques

This paper presents our knowledge-intensive Case-Based Reasoning platform for diagnosis, COBRA. It integrates domain knowledge along with cases in an ontological structure. COBRA allows users to describe cases using any concept or instance of a domain ontology, which leads to a heterogeneous case base. Cases heterogeneity complicates their retrieval since correspondences must be identified between query and case attributes. We present in this paper our system architecture and the case retrieval phase. Then, we introduce the notions of similarity regions and attributes' roles used to overcome cases heterogeneity problems.

Keywords: CAPTEURS; ONTOLOGIE; RAISONNEMENT A PARTIR DE CAS<br />---<br />CASE-BASED REASONING; ONTOLOGY; HETEROGENEOUS CASE BASE; SIMILARITY MEASURES; SIMILARITY REGIONS

Domains: Engineering Sciences [physics]

Amjad Abou Assali, Dominique Lenne, Bruno Debray. Case retrieval in ontology-based CBR systems. 32. Annual Conference on artificial intelligence (KI 2009), Sep 2009, Paderborn, Germany. pp.564-571, ⟨10.1007/978-3-642-04617-9_71⟩. ⟨ineris-00973352⟩