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An Examination of Word Stemming in Latent Semantic Index Searches

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Global Trends in Information Systems and Software Applications (ObCom 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 270))

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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.

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References

  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. Perkins, Rishel, Yenduri, Zand : Determining the Context of Text Using Augmented Latent Semantic Indexing. Journal of the American Society for Information Science, JASIS (2007)

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  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)

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© 2012 Springer-Verlag Berlin Heidelberg

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Perkins, L., Sallis, D.E., Yenduri, S. (2012). An Examination of Word Stemming in Latent Semantic Index Searches. In: Krishna, P.V., Babu, M.R., Ariwa, E. (eds) Global Trends in Information Systems and Software Applications. ObCom 2011. Communications in Computer and Information Science, vol 270. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29216-3_1

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  • DOI: https://doi.org/10.1007/978-3-642-29216-3_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29215-6

  • Online ISBN: 978-3-642-29216-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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