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Authors: Gulden Uchyigit and Keith Clark

Affiliation: Imperial College, United Kingdom

Keyword(s): Feature Selection, Text Categorization, Machine Learning.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: To improve scalability of text categorization and reduce over-fitting, it is desirable to reduce the number of words used for categorisiation. Further, it is desirable to achieve such a goal automatically without sacrificing the categorization accuracy. Such techniques are known as automatic feature selection methods. Typically this is done in the way that each word is assigned a weight (using a word scoring metric) and the top scoring words are then used to describe a document collection. There are several word scoring metrics which have been employed in literature. In this paper we present a novel feature selection method called the GU metric. The details of comparative evaluation of all the other methods are given. The results show that the GU metric outperforms some of the other well known feature selection methods.

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Paper citation in several formats:
Uchyigit, G. and Clark, K. (2007). GU METRIC - A New Feature Selection Algorithm for Text Categorization. In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-972-8865-89-4; ISSN 2184-4992, SciTePress, pages 399-402. DOI: 10.5220/0002365503990402

@conference{iceis07,
author={Gulden Uchyigit. and Keith Clark.},
title={GU METRIC - A New Feature Selection Algorithm for Text Categorization},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2007},
pages={399-402},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002365503990402},
isbn={978-972-8865-89-4},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - GU METRIC - A New Feature Selection Algorithm for Text Categorization
SN - 978-972-8865-89-4
IS - 2184-4992
AU - Uchyigit, G.
AU - Clark, K.
PY - 2007
SP - 399
EP - 402
DO - 10.5220/0002365503990402
PB - SciTePress

- Science and Technology Publications, Lda.
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