This paper describes the use of discrete graphical editing operations to dynamically fit hierarchical structural models to input data. We use the tree adjoining grammar developed by Joshi [1] as a prototypical structural model, and realise the editing process using a genetic algorithm. The novelty of our approach lies firstly in the use of the edit distance between the ordered frontier nodes of a tree and a set of dictionaries of legal labels derived from the input as a cost function. Secondly, we apply genetic algorithms to tree adjoining grammars with the introduction of a new editing operation. We demonstrate the utility of the method on a simple natural language processing problem.
CITATION STYLE
Myers, R., & Hancock, E. R. (1998). Genetic algorithms for structural editing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1451, pp. 159–168). Springer Verlag. https://doi.org/10.1007/bfb0033234
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