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Questionnaire Free Text Summarisation Using Hierarchical Classification

Lookup NU author(s): Dr Matias Garcia-Constantino


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This paper presents an investigation into the summarisation of the free text element of questionnaire data using hierarchical text classification. The process makes the assumption that text summarisation can be achieved using a classification approach whereby several class labels can be associated with documents which then constitute the summarisation. A hierarchical classification approach is suggested which offers the advantage that different levels of classification can be used and the summarisation customised according to which branch of the tree the current document is located. The approach is evaluated using free text from questionnaires used in the SAVSNET (Small Animal Veterinary Surveillance Network) project. The results demonstrate the viability of using hierarchical classification to generate free text summaries.

Publication metadata

Author(s): Garcia-Constantino MF, Coenen F, Noble PJ, Radford A

Editor(s): Max Bramer and Miltos Petridis

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Thirty-second SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence

Year of Conference: 2012

Pages: 35-48

ISSN: 9781447147381

Publisher: Springer London


DOI: 10.1007/978-1-4471-4739-8_3

Library holdings: Search Newcastle University Library for this item

ISBN: 9781447147398