Extraction-Based Single-Document Summarization Using Random Indexing

@article{Chatterjee2007ExtractionBasedSS,
  title={Extraction-Based Single-Document Summarization Using Random Indexing},
  author={Niladri Chatterjee and Shiwali Mohan},
  journal={19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007)},
  year={2007},
  volume={2},
  pages={448-455}
}
This paper presents a summarization technique for text documents exploiting the semantic similarity between sentences to remove the redundancy from the text. Semantic similarity scores are computed by mapping the sentences on a semantic space using random indexing. Random indexing, in comparison with other semantic space algorithms, presents a computationally efficient way of implicit dimensionality reduction. It involves inexpensive vector computations such as addition. It thus provides an… CONTINUE READING
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Advances in Automatic Text Summarization

  • Inderjeet Mani
  • 1999
Highly Influential
5 Excerpts

An Introduction to Latent Semantic Analysis

  • Thomas K Landauer, Peter W. Foltz, Darrell Laham
  • 45th Annual Computer Personnel Research…
  • 2004
Highly Influential
3 Excerpts

M.Tech Thesis

  • Nidhika Yadav
  • Indian Institute of Technology Delhi,
  • 2007
1 Excerpt

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