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1 Journal of Theoretical and Applied Computer Science

1 2012

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A semi-automated approach to building text summarisation classifiers

Garcia-Constantino M., Coenen F., Noble P. J., Radford A., Setzkorn C.

Journal of Theoretical and Applied Computer Science

2012

Vol. 6, nr 4

7-23

An investigation into the extraction of useful information from the free text element of questionnaires, using a semi-automated summarisation extraction technique, is described. The summarisation technique utilises the concept of classification but with the support of domain/human experts during classifier construction. A realisation of the proposed technique, SARSET (Semi-Automated Rule Summarisation Extraction Tool), is presented and evaluated using real questionnaire data. The results of this evaluation are compared against the results obtained using two alternative techniques to build text summarisation classifiers. The first of these uses standard rule-based classifier generators, and the second is founded on the concept of building classifiers using secondary data. The results demonstrate that the proposed semi-automated approach outperforms the other two approaches considered.