. German Research Center for Artificial Intelligence GmbH
. German Research Center for Artificial Intelligence GmbH
The conventional hypertext authoring framework compels authors to represent their material as an interconnected network of nodes and links. Apart from the difficulties that this alone entails, the situation with HTML is even more problematic since the author is also responsible for mapping the abstract network model onto the computer file system. This is likely to hinder the widespread adoption of HTML by information owners who are finding it difficult not only to create but also to maintain coherent documents with complex interconnection topologies.
In this paper it is argued that familiar document forms such as books, manuals, articles, reports etc. often contain sufficient structural and cross-referential cues with which to build a rich hypertextual structure. It is shown how this structure can be automatically extracted and then realised as a collection of HTML files which can be explored using generated navigation panels. The conversion process and the advantages of this approach are illustrated with interactive examples using the LaTeX2HTML converter. Other unique features of LaTeX2HTML - mathematical equations and ``conditional text'' - are also discussed.
Allowing authors to work with familiar metaphors and tools without compromising the flexibility afforded to them by the target hypertext system and delivery mechanism is perhaps the main reason for the growing popularity of text to hypertext conversion tools.
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