Analogical Transfer in RDFS, Application to Cocktail Name Adaptation

Abstract

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?

A SPARQL Query Transformation Rule Language — Application to Retrieval and Adaptation in Case-Based Reasoning

“…The cocktail name adaptation problem is how to name the adapted cocktail recipe σ(R), given the name of R (the string "Irish coffee") and the substitution σ. This issue has been addressed in [12]. It is based on an RDFS base β R associated with the recipe R and giving a (partial or complete) explanation of its name.…”