Skip to search formSkip to main content
You are currently offline. Some features of the site may not work correctly.

Multi-document summarization

Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The… Expand
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2009
Highly Cited
2009
We present an exploration of generative probabilistic models for multi-document summarization. Beginning with a simple word… Expand
  • table 1
  • figure 1
  • figure 2
  • table 2
  • table 3
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… Expand
  • figure 1
  • figure 2
  • figure 3
  • table 1
  • table 2
Highly Cited
2008
Highly Cited
2008
Multi-document summarization aims to create a compressed summary while retaining the main characteristics of the original set of… Expand
  • figure 1
  • table 1
  • table 2
  • table 3
  • figure 2
Highly Cited
2007
Highly Cited
2007
In this work we study the theoretical and empirical properties of various global inference algorithms for multi-document… Expand
  • figure 1
  • table 1
  • table 2
  • figure 3
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… Expand
  • table 1
  • table 2
  • figure 3
  • figure 4
  • figure 5
Highly Cited
2006
Highly Cited
2006
In many decision‐making scenarios, people can benefit from knowing what other people's opinions are. As more and more evaluative… Expand
Highly Cited
2004
Highly Cited
2004
We present a multi-document summarizer, MEAD, which generates summaries using cluster centroids produced by a topic detection and… Expand
  • figure 1
  • figure 2
  • table 1
  • table 2
  • figure 3
Highly Cited
2000
Highly Cited
2000
We present a multi-document summarizer, called MEAD, which generates summaries using cluster centroids produced by a topic… Expand
  • figure 1
  • table 1
  • table 2
  • table 3
  • table 4
Highly Cited
2000
Highly Cited
2000
This paper discusses a text extraction approach to multi-document summarization that builds on single-document summarization… Expand
Highly Cited
1999
Highly Cited
1999
We present a method to automatically generate a concise summary by identifying and synthesizing similar elements across related… Expand
  • figure 2
  • figure 3