Improving case retrieval using typicality

2Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper shows how typicality can be used to improve the case retrieval of a case-based reasoning (CBR) system, improving at the same time the global results of the CBR system. Typicality discriminates subclasses of a class in the domain ontology depending of how a subclass is a good example for its class. Our approach proposes to partition the subclasses of some classes into atypical, normal and typical subclasses in order to refine the domain ontology. The refined ontology allows a finergrained generalization of the query during the retrieval process. The benefits of this approach are presented according to an evaluation in the context of Taaable, a CBR system designed for the cooking domain.

Cite

CITATION STYLE

APA

Gaillard, E., Lieber, J., & Nauer, E. (2015). Improving case retrieval using typicality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9343, pp. 165–180). Springer Verlag. https://doi.org/10.1007/978-3-319-24586-7_12

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free