publisher_address = "New York, NY, 10286-1405, USA",
month = "25-29 " # jun,
organisation = "ACM SIGEVO (formerly ISGEC)",
keywords = "genetic algorithms, genetic programming, Real World
Applications, Brill tagger, experimentation, natural
language processing, languages",
abstract = "The tagging problem in natural language processing is
to find a way to label every word in a text as a
particular part of speech, e.g., proper noun. An
effective way of solving this problem with high
accuracy is the transformation-based or {"}Brill{"}
tagger. In Brill's system, a number of transformation
templates are specified a priori that are instantiated
and ranked during a greedy search-based algorithm. This
paper describes a variant of Brill's implementation
that instead uses a genetic algorithm to generate the
instantiated rules and provide an adaptive ranking.
Based on tagging accuracy, the new system provides a
better hybrid evolutionary computation solution to the
part-of-speech (POS) problem than the previous attempt.
Although not able to make up for the use of a priori
knowledge used by Brill, the method appears to point
the way for an improved solution to the tagging
problem.",
notes = "GECCO-2005 A joint meeting of the fourteenth
international conference on genetic algorithms
(ICGA-2005) and the tenth annual genetic programming
conference (GP-2005).