A Methodology for Feature Selection in Named Entity Recognition
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Date
2007
Journal Title
Journal ISSN
Volume Title
Publisher
Fountain Publishers
Abstract
In this paper a methodology for feature selection in named entity recognition is
proposed. Unlike traditional named entity recognition approaches which mainly
consider accuracy improvement as the sole objective, the innovation here is manifested
in the use of a multiobjective genetic algorithm which is employed for feature
selection basing on various aspects including error rate reduction and time taken
for evaluation, and also demonstrating the use of Pareto optimization. The proposed
method is evaluated in the context of named entity recognition, using three different
data sets and a K-nearest Neighbour machine learning algorithm. Comprehensive
experiments demonstrate the feasibility of the methodology.
Description
Chapter 7, Page 88
Keywords
Methodology, Feature Selection, Entity Recognition
Citation
Kitoogo, F. E., & Baryamureeba, V. (2007). A methodology for feature selection in named entity recognition. Strengthening the Role of ICT in Development, 88. ISBN 978-9970-02-730-9