Update Summarization Based on Latent Semantic Analysis

  • Josef Steinberger
  • Karel Ježek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5729)


This paper deals with our recent research in text summarization. We went from single-document summarization through multi-document summarization to update summarization. We describe the development of our summarizer which is based on latent semantic analysis (LSA) and propose the update summarization component which determines the redundancy and novelty of each topic discovered by LSA. The final part of this paper presents the results of our participation in the experiment of Text Analysis Conference 2008.


Singular Value Decomposition Latent Semantic Analysis Latent Semantic Indexing Model Summary Text Summarization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Josef Steinberger
    • 1
  • Karel Ježek
    • 1
  1. 1.University of West BohemiaPlzeňCzech Republic

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