Une mesure de pertinence pour le tri de l'information dans un index de fin de livre
type: Dataset
description: This paper presents the IndDoc system that assists back-of-the-book indexing. One of the indexing challenge deals with information selection: which are the most relevant headings and references. This papers shows how this selection is handled in IndDoc. It presents a metric for the ranking of headings and , for each heading, for its references.
issued: 2026-05-05T14:09:19.018840
language: fr
modified: 2026-05-05T14:09:19.018846
contact point: Organization
  fn: CCSD
keyword: conference-papers
keyword: extraction-de-termes
keyword: extraction-dinformation
keyword: infoeu-reposemanticsconferenceobject
keyword: infoinfo-aicomputer-science-csartificial-intelligence-csai
keyword: infoinfo-ircomputer-science-csinformation-retrieval-csir
keyword: sccocompcognitive-sciencecomputer-science
keyword: segmentation-thematique-de-texte

Une mesure de pertinence pour le tri de l'information dans un index de fin de livre
type: Distribution
format: HTML
issued: 2026-05-05T14:09:19.020918
modified: 2026-05-05T14:09:19.009214
access URL: https://hal.science/hal-00098057

test_moissonnage_selune
type: Agent