Maintaining case knowledge vocabulary using a new Evidential Attribute Clustering method - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2018

Maintaining case knowledge vocabulary using a new Evidential Attribute Clustering method

Résumé

Maintaining the vocabulary of case knowledge within Case Based Reasoning (CBR) presents a crucial task to ensure a high-quality problem-solving and to improve retrieval performance for large-scale CBR systems. To do, we propose, in this paper, a method that manages uncertainty while selecting the best attributes characterizing case knowledge by using belief function theory. Actually, this method is based on a new evidential attribute clustering technique to eliminate redundant and noisy attributes describing cases.
Fichier principal
Vignette du fichier
ws-procs9x6.pdf (293.31 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04433236 , version 1 (01-02-2024)

Identifiants

  • HAL Id : hal-04433236 , version 1

Citer

Safa Ben Ayed, Zied Elouedi, Eric Lefevre. Maintaining case knowledge vocabulary using a new Evidential Attribute Clustering method. 13th International conference on data science and knowledge engineering for sensing decision support, FLINS'2018, Aug 2018, Belfast (Northern Ireland), United Kingdom. pp.347-354. ⟨hal-04433236⟩

Collections

UNIV-ARTOIS LGI2A
2 Consultations
1 Téléchargements

Partager

Gmail Facebook X LinkedIn More