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Fast Big Textual Data Parsing in Distributed and Parallel Computing Environment

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Mobile, Ubiquitous, and Intelligent Computing

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 274))

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Abstract

Currently, tremendous numbers of scientific and technical articles are being published due to the rapid development of the scientific and technical fields. Also, systems are being proposed which can give useful information to users by extracting information from scientific and technical articles. For such systems, we need to be able to extract information from a massive number of documents very fast and reliably. However, legacy parsers, such as Stanford, Enju and so on, cannot consider a large number of documents because such parsers analyze wide context range of the sentence for their parsing, and so those parsers require a lot of time to run. Therefore, in this paper, we report on the development of a parser which is based on MapReduce, a distributed and parallel programming model. Our parser has achieved about nineteen times better performance than that of one of the-state-of-the-art legacy parsers.

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Authors and Affiliations

  1. Dept. of Computer Intelligence Research, Korea Institute of Science and Technology Information, 245 Daehakno, Yuseong-gu, Daejeon, 305-806, Korea

    Jung-Ho Um, Chang-Hoo Jeong, Sung-Pil Choi, Seungwoo Lee & Hanmin Jung

Authors
  1. Jung-Ho Um
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  2. Chang-Hoo Jeong
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  3. Sung-Pil Choi
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  4. Seungwoo Lee
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  5. Hanmin Jung
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Corresponding author

Correspondence to Jung-Ho Um .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Seoul University of Science & and Technology (SeoulTech), Seoul, Korea, Republic of (South Korea)

    James J. (Jong Hyuk) Park

  2. Biomedical Informatics Neuroscience, Ohio State University Center for Biomedical Engineering, Columbus, Ohio, USA

    Hojjat Adeli

  3. Dept of Computer Education, Jeju National University Teachers College, Jeju Special Self-Governing Province, Korea, Republic of (South Korea)

    Namje Park

  4. Ryerson University Dept. Computer Science, Toronto, Ontario, Canada

    Isaac Woungang

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© 2014 Springer-Verlag Berlin Heidelberg

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Um, JH., Jeong, CH., Choi, SP., Lee, S., Jung, H. (2014). Fast Big Textual Data Parsing in Distributed and Parallel Computing Environment. In: Park, J., Adeli, H., Park, N., Woungang, I. (eds) Mobile, Ubiquitous, and Intelligent Computing. Lecture Notes in Electrical Engineering, vol 274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40675-1_41

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  • DOI: https://doi.org/10.1007/978-3-642-40675-1_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40674-4

  • Online ISBN: 978-3-642-40675-1

  • eBook Packages: EngineeringEngineering (R0)

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