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A Hybrid Methodology of Effective Text-Similarity Evaluation

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New Trends in Computer Technologies and Applications (ICS 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1013))

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Abstract

In this paper, an effective methodology which hybridizes a LCS finding algorithm and SimHash computation is presented for evaluating the text-similarity of articles. It reduces the time-space scale needed by the LCS algorithm by breaking the articles into word subsequences of sentences, managing and pairing them by SimHash comparisons, and reaching the goal of evaluating long-length articles rapidly, with the similar parts and similarity score of compared articles figured out exactly.

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Author information

Authors and Affiliations

  1. National Chiao-Tung University, No. 1001, Daxue Rd., Hsinchu, 300, Taiwan (R.O.C.)

    Shu-Kai Yang & Chien Chou

Authors
  1. Shu-Kai Yang
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  2. Chien Chou
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Corresponding author

Correspondence to Shu-Kai Yang .

Editor information

Editors and Affiliations

  1. National Yunlin University of Science and Technology, Douliu, Taiwan

    Chuan-Yu Chang

  2. National Yunlin University of Science and Technology, Douliu, Taiwan

    Chien-Chou Lin

  3. Southern Taiwan University of Science and Technology, Tainan, Taiwan

    Horng-Horng Lin

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Cite this paper

Yang, SK., Chou, C. (2019). A Hybrid Methodology of Effective Text-Similarity Evaluation. In: Chang, CY., Lin, CC., Lin, HH. (eds) New Trends in Computer Technologies and Applications. ICS 2018. Communications in Computer and Information Science, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-13-9190-3_24

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  • DOI: https://doi.org/10.1007/978-981-13-9190-3_24

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9189-7

  • Online ISBN: 978-981-13-9190-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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