Evolving Lucene search queries for text classification

HIRSCH, Laurence, SAEEDI, M and HIRSCH, R (2007). Evolving Lucene search queries for text classification. In: Genetic and Evolutionary Computation Conference, London, 7-11 July.

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Abstract

We describe a method for generating accurate, compact, human understandable text classifiers. Text datasets are indexed using Apache Lucene and Genetic Programs are used to construct Lucene search queries. Genetic programs acquire fitness by producing queries that are effective binary classifiers for a particular category when evaluated against a set of training documents. We describe a set of functions and terminals and provide results from classification tasks.

Item Type:	Conference or Workshop Item (Paper)
Research Institute, Centre or Group - Does NOT include content added after October 2018:	Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
Departments - Does NOT include content added after October 2018:	Faculty of Science, Technology and Arts > Department of Computing
Depositing User:	Laurence Hirsch
Date Deposited:	25 Feb 2013 16:29
Last Modified:	18 Mar 2021 14:07
URI:	https://shura.shu.ac.uk/id/eprint/6624

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