E. Korkmaz, and G. Ucoluk. 2001 Genetic and Evolutionary Computation Conference
Late Breaking Papers, page 245--251. San Francisco, California, USA, (9-11 July 2001)
Abstract
There has been a big interest in inducing classes of
grammars in the area of machine learning. Various
attempts have been carried out for automatically
inferring different grammar classes. The symbolic
nature of the grammar induction problem makes it
suitable for the GP-approach. However the
straightforward application of the GP method on Context
Free Grammar Induction problem fails to generate a
satisfactory solution. The interdependency among
subparts of a CFG is high and it seems to be the reason
that prevents the GP method from finding out effective
building blocks during the search. In this paper a new
approach is presented where the aim is to formalize a
control module for the genetic search which can use the
interdependency information existing in CFGs and hence
can direct the search only among well-fit grammars in
the search space.
%0 Conference Paper
%1 korkmaz:2001:gpgi
%A Korkmaz, Emin Erkan
%A Ucoluk, Gokturk
%B 2001 Genetic and Evolutionary Computation Conference
Late Breaking Papers
%C San Francisco, California, USA
%D 2001
%E Goodman, Erik D.
%K C4.5 CFG, English NLP, algorithms, context free genetic grammar induction, programming,
%P 245--251
%T Genetic Programming for Grammar Induction
%U http://citeseer.ist.psu.edu/451812.html
%X There has been a big interest in inducing classes of
grammars in the area of machine learning. Various
attempts have been carried out for automatically
inferring different grammar classes. The symbolic
nature of the grammar induction problem makes it
suitable for the GP-approach. However the
straightforward application of the GP method on Context
Free Grammar Induction problem fails to generate a
satisfactory solution. The interdependency among
subparts of a CFG is high and it seems to be the reason
that prevents the GP method from finding out effective
building blocks during the search. In this paper a new
approach is presented where the aim is to formalize a
control module for the genetic search which can use the
interdependency information existing in CFGs and hence
can direct the search only among well-fit grammars in
the search space.
@inproceedings{korkmaz:2001:gpgi,
abstract = {There has been a big interest in inducing classes of
grammars in the area of machine learning. Various
attempts have been carried out for automatically
inferring different grammar classes. The symbolic
nature of the grammar induction problem makes it
suitable for the GP-approach. However the
straightforward application of the GP method on Context
Free Grammar Induction problem fails to generate a
satisfactory solution. The interdependency among
subparts of a CFG is high and it seems to be the reason
that prevents the GP method from finding out effective
building blocks during the search. In this paper a new
approach is presented where the aim is to formalize a
control module for the genetic search which can use the
interdependency information existing in CFGs and hence
can direct the search only among well-fit grammars in
the search space.},
added-at = {2008-06-19T17:35:00.000+0200},
address = {San Francisco, California, USA},
author = {Korkmaz, Emin Erkan and Ucoluk, Gokturk},
biburl = {https://www.bibsonomy.org/bibtex/27fe3e3deadee0bcda48ff6dc399a568e/brazovayeye},
booktitle = {2001 Genetic and Evolutionary Computation Conference
Late Breaking Papers},
editor = {Goodman, Erik D.},
interhash = {3bf827bc0174c5ce7cbdb25a77b12e25},
intrahash = {7fe3e3deadee0bcda48ff6dc399a568e},
keywords = {C4.5 CFG, English NLP, algorithms, context free genetic grammar induction, programming,},
month = {9-11 July},
notes = {GECCO-2001LB},
pages = {245--251},
timestamp = {2008-06-19T17:43:38.000+0200},
title = {Genetic Programming for Grammar Induction},
url = {http://citeseer.ist.psu.edu/451812.html},
year = 2001
}