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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Kohonen, T.: Exploration of very large databases by self-organizing maps. In: Proceedings of ICNN 1997, International Conference on Neural Networks. PL1-PL6. IEEE Service Center, Piscataway (1997a)
Kohonen, T.: Self-Organizing Maps. Springer Series in Information Science (1997b)
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kauffmann, Los Altos (1993)
Quinlan, J.R.: Data Mining Tools See5 and C5.0, (2002), http://www.rulequest.com/see5-info.html
Mitchell, T.M.: Machine Learning. McGraw-Hill, New York (1997)
Schreibman, S.: The MacGreevy Archive (1998), http://www.ucd.ie/~cosei/archive.html
Schreibman, S.: The MacGreevy Archive (2000), http://jafferson.villiage.Virginia.edu/-macgreevy
Bosak, J.: The Plays of Shakespeare in XML (1999), http://www.oasis-open.org/cover/bosakShakespeare200.html
Schreibman, S.: Early American Digital Archives, Hosted by Maryland Institute of Technology (2003), http://www.mith.umd.edu
Hellman, E., Ephron, D., Poindexter, M.: Openly Informatics Inc. (1999-2000), http://www.openly.com/efirst
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
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, Heidelberg. https://doi.org/10.1007/978-3-540-39398-6_4
Download citation
DOI: https://doi.org/10.1007/978-3-540-39398-6_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20024-6
Online ISBN: 978-3-540-39398-6
eBook Packages: Springer Book Archive