Cascading XSL filters for content selection in multilingual document generation

Authors:
Guillermo Barrutieta;Joseba Abaitua;JosuKa Díaz
Affiliations:
Mondragon Unibertsitatea, Arrasate, Spain;Avenida de las Universidades, Bilbao, Spain;Avenida de las Universidades, Bilbao, Spain
Venue:
NLPXML '02 Proceedings of the 2nd workshop on NLP and XML - Volume 17
Year:
2002

Citing 5
Cited 1

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Abstract

Content selection is a key factor of any successful document generation system. This paper shows how a content selection algorithm has been implemented using an efficient combination of XML/XSL technology and the framework of RST for discourse modeling. The system generates multilingual documents adapted to user profiles in a learning environment for the web. This CourseViewGenerator applies simplified RST schemes to the elaboration of a master document in XML from which content segments are chosen to suit the user's needs. The personalisation of the document is achieved through the application of a sequence of filtering levels of text selection based on the user aspects given as input. These cascading filters are implemented in XSL.