Genetic algorithms for structural editing

  • Richard Myers
  • Edwin R. Hancock
Structural Matching and Grammatical Inference
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1451)


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 [l] 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.


Genetic Algorithm Edit Distance Parse Tree Editing Operation Labelling Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1998

Authors and Affiliations

  • Richard Myers
    • 1
  • Edwin R. Hancock
    • 1
  1. 1.Department of Computer ScienceUniversity of YorkYorkUK

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