The French Correction: When Retrieval is Harder to Specify than Adaptation

Yves Lepage (1) , Jean Lieber (2) , Isabelle Mornard (3, 4) , Emmanuel Nauer (2) , Julien Romary (2) , Reynault Sies (2)

1 Waseda University [Tokyo, Japan]
2 Data Science, Knowledge, Reasoning and Engineering - K team
3 Inria Nancy - Grand Est
4 UJM - Université Jean Monnet - Saint-Étienne

A common idea in the eld of case-based reasoning is that the retrieval step can be specied by the use of some similarity measure: the retrieved cases maximize the similarity to the target problem and, then, the adaptation step has to take into account the mismatches between the retrieved cases and the target problem in order to solve this latter. The use of this methodological schema for the application described in this paper has proven to be non ecient. Indeed, designing a retrieval procedure without the precise knowledge of the adaptation procedure has not been possible. The domain of this application is the correction of French sentences: a problem is an incorrect sentence and a valid solution is a correction of this problem. Adaptation consists in solving an analogical equation that enables to execute the correction of the retrieved case on the target problem. Thus, retrieval has to ensure that this application is feasible. The rst version of such a retrieval procedure is described and evaluated: it is a knowledge-light procedure that does not use linguistic knowledge about French.

Mots clés: case-based reasoning; retrieval; analogy; sentence correction

Domaines: Intelligence artificielle [cs.AI]

Yves Lepage, Jean Lieber, Isabelle Mornard, Emmanuel Nauer, Julien Romary, et al.. The French Correction: When Retrieval is Harder to Specify than Adaptation. ICCBR 2020 - 28th International Conference on Case-Based Reasoning, Jun 2020, Salamanca / Virtual, Spain. pp.15, ⟨10.1007/978-3-030-58342-2_20⟩. ⟨hal-02964141⟩