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An Examination of Word Stemming in Latent Semantic Index Searches

  • Louise Perkins
  • David E. Sallis
  • Sumanth Yenduri
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 270)

Abstract

In this paper we describe an application with large geographic data sets that was improved using Latent Semantic Analysis (LSA) in combination with word stemming. The results are consistent with other published works, and demonstrate value added skill.

Keywords

Latent Semantic Analysis Crystalline Lens Latent Semantic Index Word Stem Metadata Record 
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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References

  1. 1.
    Kolda, T.G., O’Leary, D.P.: Computation and uses of the semidiscrete matrix decomposition. Technical Report Number ORNL-TM-13766, Oak Ridge National Laboratory, Oak Ridge, TN (April 1999), http://csmr.ca.sandia.gov/~tgkolda/ref#ORNL-TM-13766
  2. 2.
    Perkins, Rishel, Yenduri, Zand : Determining the Context of Text Using Augmented Latent Semantic Indexing. Journal of the American Society for Information Science, JASIS (2007)Google Scholar
  3. 3.
    Rishel, Perkins, Yenduri, Zand, Iyengar.: Augmentation of a Term/Document Matrix with Part-of-Speech Tags to Improve Accuracy of Latent Semantic Analysis. WSEAS Transactions on Computers 5(6), 1361–1366 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Louise Perkins
    • 1
  • David E. Sallis
    • 1
  • Sumanth Yenduri
    • 1
  1. 1.The University of Southern MississippiLong BeachUSA

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