A scaleable multi-document centroid-based summarizer

Authors:
Dragomir Radev;Timothy Allison;Matthew Craig;Stanko Dimitrov;Omer Kareem;Michael Topper;Adam Winkel;Jin Yi
Affiliations:
University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI;University of Michigan, Ann Arbor, MI
Venue:
HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
Year:
2004

Citing 3
Cited 0

Generating natural language summaries from multiple on-line sources

Computational Linguistics - Special issue on natural language generation
NewsInEssence: a system for domain-independent, real-time news clustering and multi-document summarization

HLT '01 Proceedings of the first international conference on Human language technology research
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

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Abstract

We are presenting the most recent version of MEAD (v. 3.08), a large-scale public-domain summarizer that has been used in a number of applications, including the 2001 JHU summer workshop and the NewsInEssence project (www.newsinessence.com). A version of MEAD finished in first place on task 4 at DUC 2003 and finished in the top three on two other tasks.