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Semantic Software Lab
Concordia University
Montréal, Canada

Next-Generation Summarization: Contrastive, Focused, and Update Summaries

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TitleNext-Generation Summarization: Contrastive, Focused, and Update Summaries
Publication TypeConference Paper
Year of Publication2007
AuthorsWitte, R., and S. Bergler
Refereed DesignationRefereed
Conference NameInternational Conference on Recent Advances in Natural Language Processing (RANLP 2007)
Date PublishedSeptember 27–29
Conference LocationBorovets, Bulgaria

Classical multi-document summaries focus on the common topics of a document set and omit distinctive themes particular to a single document—thereby often suppressing precisely that kind of information a user might need for a specific task. This can be avoided through advanced multi-document summaries that take a user's context and history into account, by delivering focused, contrastive, or update summaries. To facilitate the generation of these different summaries, we propose to generate all types from a single data structure, topic clusters, which provide for an abstract representation of a set of documents. Evaluations carried out on five years' worth of data from the DUC summarization competition prove the feasibility of this approach.


Copyright © 2007 René Witte and Sabine Bergler

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