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Conference Papers Year : 2016

Analogical Transfer in RDFS, Application to Cocktail Name Adaptation

Abstract

This paper deals with analogical transfer in the framework of the representation language RDFS. The application of analogical transfer to case-based reasoning consists in reusing the problem-solution dependency to the context of the target problem; thus it is a general approach to adaptation. RDFS is a representation language that is a standard of the semantic Web; it is based on RDF, a graphical representation of data, completed by an entailment relation. A dependency is therefore represented as a graph representing complex links between a problem and a solution, and analogical transfer uses, in particular, RDFS entailment. This research work is applied (and inspired from) the issue of cocktail name adaptation: given a cocktail and a way this cocktail is adapted by changing its ingredient list, how can the cocktail name be modified?
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Dates and versions

hal-01410237 , version 1 (06-12-2016)

Identifiers

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Nadia Kiani, Jean Lieber, Emmanuel Nauer, Jordan Schneider. Analogical Transfer in RDFS, Application to Cocktail Name Adaptation. International Conference on Case-Based Reasoning (ICCBR-2016), Oct 2016, Atlanta, United States. pp.218 - 233, ⟨10.1007/978-3-319-47096-2_15⟩. ⟨hal-01410237⟩
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