Akhtar, Shazia and Reilly, Ronan and Dunnion, John (2003) Auto-tagging of Text Documents into XML. In: TSD 2003: Text, Speech and Dialogue. Lecture Notes in Computer Science (LNCS) (2807). Springer, pp. 20-26. ISBN 354020024X

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Abstract

In this paper we present a novel system which automatically converts text documents into XML by extracting information from previously tagged XML documents. The system uses the Self-Organizing Map (SOM) learning algorithm to arrange tagged documents on a two-dimensional map such that nearby locations contain similar documents. It then employs the inductive learning algorithm C5.0 to automatically extract and apply auto-tagging rules from the nearest SOM neighbours of an untagged document. The system is designed to be adaptive, so that once a document is tagged in XML, it learns from its errors in order to improve accuracy. The automatically tagged documents can be categorized on the SOM, further improving the map’s resolution. Various experiments were carried out on our system, using documents from a number of different domains. The results show that our approach performs well with impressive accuracy.

Item Type:	Book Section
Additional Information:	Cite this paper as: Akhtar S., Reilly R.G., Dunnion J. (2003) Auto-tagging of Text Documents into XML. In: Matoušek V., Mautner P. (eds) Text, Speech and Dialogue. TSD 2003. Lecture Notes in Computer Science, vol 2807. Springer, Berlin, Heidelber
Keywords:	Auto-tagging; Text Documents; XML; Self-Organizing Map (SOM); learning algorithm;
Academic Unit:	Faculty of Science and Engineering > Computer Science
Item ID:	8214
Identification Number:	https://doi.org/10.1007/978-3-540-39398-6_4
Depositing User:	Prof. Ronan Reilly
Date Deposited:	15 May 2017 14:42
Publisher:	Springer
Refereed:	Yes
URI:	http://link.springer.com
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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