Using NLP to build the hypertextuel network of a back-of-the-book index
<|reference_start|>Using NLP to build the hypertextuel network of a back-of-the-book index: 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.<|reference_end|>
@article{mekki2006using,
    title={Using NLP to build the hypertextuel network of a back-of-the-book index},
    author={Touria A"it El Mekki (LIPN), Adeline Nazarenko (LERIA)},
    journal={Proceedings of the International Conference on Recent Advances in
  Natural Language Processing (RANLP) (2005) 316-320},
    year={2006},
    archivePrefix={arXiv},
    eprint={cs/0609134},
    primaryClass={cs.AI cs.IR}
}