ML p(r)ior | Towards a More User-friendly Correction

Towards a More User-friendly Correction

We first present our view of detection and correction of syntactic errors. We then introduce a new correction method, based on heuristic criteria used to decide which correction should be preferred. Weighting of these criteria leads to a flexible and parametrable system, which can adapt itself to the user. A partitioning of the trees based on linguistic criteria: agreement rules, rather than computational criteria is then necessary. We end by proposing extensions to lexical correction and to some syntactic errors. Our aim is an adaptable and user-friendly system capable of automatic correction for some applications.

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