Retrieval based on self-explicative memories

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

One of the key issues in Case-Based Reasoning (CBR) systems is the efficient retrieval of cases when the case base is huge and/or it contains uncertainty and partial knowledge. We tackle these issues by organizing the case memory using an unsupervised clustering technique to identify data patterns for promoting all CBR steps. Moreover, another useful property of these patterns is that they provide to the user additional information about why the cases have been selected and retrieved through symbolic descriptions. This work analyses the introduction of this knowledge in the retrieve phase. The new strategies improve the case retrieval configuration procedure.

Idioma originalInglés
Título de la publicación alojadaAdvances in Case-Based Reasoning - 9th European Conference, ECCBR 2008, Proceedings
Páginas210-224
Número de páginas15
DOI
EstadoPublicada - 2008
Evento9th European Conference on Case-Based Reasoning, ECCBR 2008 - Trier, Alemania
Duración: 1 sept 20084 sept 2008

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen5239 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia9th European Conference on Case-Based Reasoning, ECCBR 2008
País/TerritorioAlemania
CiudadTrier
Período1/09/084/09/08

Huella

Profundice en los temas de investigación de 'Retrieval based on self-explicative memories'. En conjunto forman una huella única.

Citar esto