Extracting multi-document summaries with a double clustering approach

Authors:
Sara Botelho Silveira;António Branco
Affiliations:
University of Lisbon, Portugal,Edifício C6, Departamento de Informática Faculdade de Ciências, Universidade de Lisboa Campo Grande, Lisboa, Portugal;University of Lisbon, Portugal,Edifício C6, Departamento de Informática Faculdade de Ciências, Universidade de Lisboa Campo Grande, Lisboa, Portugal
Venue:
NLDB'12 Proceedings of the 17th international conference on Applications of Natural Language Processing and Information Systems
Year:
2012

Citing 9
Cited 2

The use of MMR, diversity-based reranking for reordering documents and producing summaries

Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
New Methods in Automatic Extracting

Journal of the ACM (JACM)
Multidocument summarization via information extraction

HLT '01 Proceedings of the first international conference on Human language technology research
From single to multi-document summarization: a prototype system and its evaluation

ACL '02 Proceedings of the 40th Annual Meeting on Association for 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
A suite of shallow processing tools for Portuguese: LX-suite

EACL '06 Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Posters & Demonstrations
The automatic creation of literature abstracts

IBM Journal of Research and Development
GistSumm: a summarization tool based on a new extractive method

PROPOR'03 Proceedings of the 6th international conference on Computational processing of the Portuguese language
Out-of-the-box robust parsing of Portuguese

PROPOR'10 Proceedings of the 9th international conference on Computational Processing of the Portuguese Language

Combining co-clustering with noise detection for theme-based summarization

ACM Transactions on Speech and Language Processing (TSLP)
Editorial: COMPENDIUM: A text summarization system for generating abstracts of research papers

Data & Knowledge Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a method for extractive multi-document summarization that explores a two-phase clustering approach. First, sentences are clustered by similarity, and one sentence per cluster is selected, to reduce redundancy. Then, in order to group them according to topics, those sentences are clustered considering the collection of keywords. Additionally, the summarization process further includes a sentence simplification step, which aims not only to create simpler and more incisive sentences, but also to make room for the inclusion of relevant content in the summary as much as possible.