Using NLP to build the hypertextuel network of a back-of-the-book index

Details Using NLP to build the hypertextuel network of a back-of-the-book index Using NLP to build the hypertextuel network of a back-of-the-book index

2006-09-24

arxiv.org/abs/cs/0609134v1

Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP) (2005) 316-320

Computer Science

Artificial Intelligence

Scientific paper

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.

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