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Integrating Knowledge from Different Sources for Automatic Back-of-the-book Indexing

Authors: Lyne Da Sylva;

Integrating Knowledge from Different Sources for Automatic Back-of-the-book Indexing

Abstract

The paper reports research on automatic back-of-the-book indexing. It presents a methodology which brings together knowledge from different disciplines. It is inspired by human indexing methodology and the results are more similar to manually-crafted indexes than those produced by previous automatic approaches. Issues of evaluation and applications are addressed.Cette communication présente les résultats de recherche sur l'indexation automatique de livres. L'étude propose une méthodologie qui rassemble des sources de connaissances provenant de disciplines différentes. La méthodologie s'inspire de l'indexation humaine et les résultats se rapprochent plus de l'indexation manuelle que les autres méthodes d'indexation automatique. Sont également touchés les enjeux d'évaluation et d'applicabilité.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
gold