Multi-document summarization

Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The… (More)
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Review
2017
Review
2017
In recent years, there has been a explosion in the amount of text data from a variety of sources. This volume of text is an… (More)
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Highly Cited
2013
Highly Cited
2013
This paper presents G-FLOW, a novel system for coherent extractive multi-document summarization (MDS).1 Where previous work on… (More)
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Highly Cited
2009
Highly Cited
2009
We present an exploration of generative probabilistic models for multi-document summarization. Beginning with a simple word… (More)
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Highly Cited
2009
Highly Cited
2009
Most of the existing multi-document summarization methods decompose the documents into sentences and work directly in the… (More)
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Highly Cited
2008
Highly Cited
2008
Extraction based Multi-Document Summarization Algorithms consist of choosing sentences from the documents using some weighting… (More)
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Highly Cited
2008
Highly Cited
2008
The Markov Random Walk model has been recently exploited for multi-document summarization by making use of the link relationships… (More)
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Highly Cited
2007
Highly Cited
2007
Topic-focused multi-document summarization aims to produce a summary biased to a given topic or user profile. This paper presents… (More)
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Highly Cited
2005
Highly Cited
2005
The problem of using topic representations for multi-document summarization (MDS) has received considerable attention recently… (More)
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Highly Cited
2004
Highly Cited
2004
Since we began participating in DUC in 2001, our summarizer has been based on an HMM (Hidden Markov Model) for sentence selection… (More)
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Highly Cited
2000
Highly Cited
2000
This paper discusses a text extraction approach to multidocument summarization that builds on single-document summarization… (More)
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