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A Study on Improved Similarity Measure Algorithm for Text-Based Document

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Future Generation Information Technology (FGIT 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7709))

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Abstract

A study on the similarity measurement of document has been active. We can move the position of word within the sentence. But from these steps, the probability of the meaning change is extremely rare. Existing research methods are not enough studies of these parts and the overall accuracy goes down. Therefore, in this paper, we proposed the algorithm that is improved the accuracy of the similarity measurement algorithm through moving to the words in the sentence.

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References

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Author information

Authors and Affiliations

  1. Department of Medical IT and Marketing, Eulji University, Seongnam, Korea

    Ki-Young Lee & Il-Hee Seo

  2. Department of Computer Science and Information Engineering, KonKuk University, Seoul, Korea

    Jeong-Joon Kim

  3. Department of Electronic Communication, Dongyang Mirae University, Seoul, Korea

    Eun-Young Kang

  4. Department of Internet, Chungwoon University, Hongseong, Chungnam, Korea

    Jong-Jin Park

Authors
  1. Ki-Young Lee
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  2. Il-Hee Seo
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  3. Jeong-Joon Kim
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  4. Eun-Young Kang
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  5. Jong-Jin Park
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Editor information

Editors and Affiliations

  1. GVSA and University of Tasmania, Hobart, TAS, Australia

    Tai-hoon Kim

  2. Hannam University, Daejeon, South Korea

    Young-hoon Lee

  3. National Chiao Tung University, Hsinchu, Taiwan, ROC

    Wai-chi Fang

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© 2012 Springer-Verlag Berlin Heidelberg

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Lee, KY., Seo, IH., Kim, JJ., Kang, EY., Park, JJ. (2012). A Study on Improved Similarity Measure Algorithm for Text-Based Document. In: Kim, Th., Lee, Yh., Fang, Wc. (eds) Future Generation Information Technology. FGIT 2012. Lecture Notes in Computer Science, vol 7709. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35585-1_25

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  • DOI: https://doi.org/10.1007/978-3-642-35585-1_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35584-4

  • Online ISBN: 978-3-642-35585-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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