Filtering for profile-biased multi-document summarization

Authors:
Sana Leila Châar;Olivier Ferret;Christian Fluhr
Affiliations:
CEA-LIST/LIC2M, Fontenay-aux-Roses Cedex;CEA-LIST/LIC2M, Fontenay-aux-Roses Cedex;CEA-LIST/LIC2M, Fontenay-aux-Roses Cedex
Venue:
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Year:
2005

Citing 6
Cited 0

Accurate user directed summarization from existing tools

Proceedings of the seventh international conference on Information and knowledge management
Advances in domain independent linear text segmentation

NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Automatic evaluation of summaries using N-gram co-occurrence statistics

NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Query-relevant summarization using FAQs

ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Multi-answer-focused multi-document summarization using a question-answering engine

COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies

NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.