Filtering for Profile-Biased Multi-document Summarization

Sana Leila Châar (1) , Olivier Ferret (1) , Christian Fluhr (1)

1 LIC2M - Laboratoire Ingénierie de la Connaissance Multimédia Multilingue

In this article, we present an information filtering method that selects from a set of documents their most significant excerpts in relation to a user profile. This method relies on both structured profiles and a topical analysis of documents. The topical analysis is also used for expanding a profile in relation to a particular document by selecting the terms of the document that are closely linked to those of the profile. This expansion is a way for selecting in a more reliable way excerpts that are linked to profiles but also for selecting excerpts that may bring new and interesting information about their topics. This method was implemented by the REDUIT system, which was successfully evaluated for document filtering and passage extraction.

Mots clés: résumé automatique

Domaines: Recherche d'information [cs.IR]

Sana Leila Châar, Olivier Ferret, Christian Fluhr. Filtering for Profile-Biased Multi-document Summarization. 27th European Conference on IR Research (ECIR 2005), Mar 2005, Santiago de Compostela, Spain. pp.127-141, ⟨10.1007/b107096⟩. ⟨cea-00179711⟩