Components for Case-Based Reasoning Systems

Authors:
Chema Abasolo;Enric Plaza;Josep Lluís Arcos
Affiliations:
-;-;-
Venue:
CCIA '02 Proceedings of the 5th Catalonian Conference on AI: Topics in Artificial Intelligence
Year:
2002

Citing 6
Cited 1

Simplifying decision trees

International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
A Distance-Based Attribute Selection Measure for Decision Tree Induction

Machine Learning
Case-based reasoning: foundational issues, methodological variations, and system approaches

AI Communications
Induction of Decision Trees

Machine Learning
Constructive Adaptation

ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
Similarity Assessment for Relational CBR

ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development

A fault diagnosis application based on a combination case-based reasoning and ontology approach

International Journal of Knowledge-based and Intelligent Engineering Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we present CAT-CBR a component-based platform for developing CBR systems. CAT-CBR uses UPML (Universal Problem-solving Methods Language) for specifying CBR components. A collection of CBR components for retrieval of propositional cases is presented in detail. The CAT-CBR platform guides the engineer using a case-based recommendations system to develop a configuration of components that satisfies the requirements of a CBR system application. We also present how to develop a runtime CBR application from the configuration resultant of the configuring process.