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Quality of Semantic Compression in Classification

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Computational Collective Intelligence. Technologies and Applications (ICCCI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6421))

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Abstract

Article presents results of implementation of semantic compression for English. An idea of semantic compression is reintroduced with examples and steps taken to perform experiment are given. A task of re-engineering available structures in order to apply them to already existing project infrastructure for experiments is described. Experiment demonstrates validity of research along with real examples of semantically compressed documents.

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References

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Author information

Authors and Affiliations

  1. Poznan School of Banking, Poland

    Dariusz Ceglarek

  2. Poznan University of Economics, Poland

    Konstanty Haniewicz

  3. Business Consulting Center, Poland

    Wojciech Rutkowski

Authors
  1. Dariusz Ceglarek
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  2. Konstanty Haniewicz
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  3. Wojciech Rutkowski
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Editor information

Editors and Affiliations

  1. Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, 415 Chien-Kung Road, 807, Kaohsiung, Taiwan

    Jeng-Shyang Pan

  2. Department of Computer Science and Information Engineering, National Taiwan University of Science and Technology, #43, Sec.4, Keelung Rd., 106, Taipei, Taiwan

    Shyi-Ming Chen

  3. Institute of Informatics, Wroclaw University of Technology, Str. Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

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Ceglarek, D., Haniewicz, K., Rutkowski, W. (2010). Quality of Semantic Compression in Classification. In: Pan, JS., Chen, SM., Nguyen, N.T. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2010. Lecture Notes in Computer Science(), vol 6421. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16693-8_18

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  • DOI: https://doi.org/10.1007/978-3-642-16693-8_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16692-1

  • Online ISBN: 978-3-642-16693-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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