  Relying on the idea that back-of-the-book indexes are traditional devices for
navigation through large documents, we have developed a method to build a
hypertextual network that helps the navigation in a document. Building such an
hypertextual network requires selecting a list of descriptors, identifying the
relevant text segments to associate with each descriptor and finally ranking
the descriptors and reference segments by relevance order. We propose a
specific document segmentation method and a relevance measure for information
ranking. The algorithms are tested on 4 corpora (of different types and
domains) without human intervention or any semantic knowledge.
