A Presentation Architecture for Individualized Content


A modern approach for generating individualized web-sites is to compose a page out of individual elements, for instance XML-fragments, which is eventually transformed to HTML. If the generated pages differ for each user, then the required transformation processes put a heavy load on the server, hence slowing down response times significantly.
The learning environment ActiveMath uses this composing approach to generate learning courses that suit best the needs and goals of the individual learner. For instance, depending on their current knowledge, different users that learn the same content get presented courses that differ in length and in amount and difficulty of exercises and examples. Currently, the learning materials are transformed in one step from XML to HTML (or other output formats).
The learning materials are encoded in a language called OMDoc which encodes semantically the fragments as well as the mathematical formulae. This article hence provides an approach to the answer “How can Semantic Web technology be used to improve adaptation and information retrieval?”. Moreover the ability to generate multiple output formats from the same content source is a central requirement of the architecture. It provides a first step towards device adaptation providing, currently, an on-screen HTML version and a printable PDF version.
This article describes the architecture we developed to solve the performance problems that arouse out of the page generation process. In this architecture, the generation process is divided into several layers, with each layer adding/transforming well-specified data. Among other advantages, this approach allows caching of individual transformed fragments. We hope that in this way the performance problems can be reduced.


[PDF]PresentationArch_IndividualizedContent_AH-WWW-2003.pdfFinal version