RNTI

MODULAD
Résumé interactif de documents
In EGC 2024, vol. RNTI-E-40, pp.449-456
Abstract
With the advent of modern chatbots, automatic summarization is becoming common practice to quicken access to information. However the summaries they generate can be biased, unhelpful or even untruthful. Hence, in sensitive scenarios (e.g. summarizing scientific articles or press articles), extractive summarization remains a more reliable approach. In this paper we present an original extractive method coupled with a user-friendly interface that allows for interactive summarization.