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Self–Organizing Map Representation for Clustering Wikipedia Search Results

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Intelligent Information and Database Systems (ACIIDS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6592))

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Abstract

The article presents an approach to automated organization of textual data. The experiments have been performed on selected sub-set of Wikipedia. The Vector Space Model representation based on terms has been used to build groups of similar articles extracted from Kohonen Self-Organizing Maps with DBSCAN clustering. To warrant efficiency of the data processing, we performed linear dimensionality reduction of raw data using Principal Component Analysis. We introduce hierarchical organization of the categorized articles changing the granularity of SOM network. The categorization method has been used in implementation of the system that clusters results of keyword-based search in Polish Wikipedia.

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Author information

Authors and Affiliations

  1. Department of Computer Systems Architecture, Gdańsk University of Technology, Poland

    Julian Szymański

Authors
  1. Julian Szymański
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Editor information

Editors and Affiliations

  1. Wroclaw University of Technology, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Department of Computer Engineering, Yeungnam University, Dae-Dong, 712-749, Gyeungsan, Korea

    Chong-Gun Kim

  3. Institute of Informatics, Automation and Robotics, Wroclaw University of Technology, 50-370, Wrocław, Poland

    Adam Janiak

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Szymański, J. (2011). Self–Organizing Map Representation for Clustering Wikipedia Search Results. In: Nguyen, N.T., Kim, CG., Janiak, A. (eds) Intelligent Information and Database Systems. ACIIDS 2011. Lecture Notes in Computer Science(), vol 6592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20042-7_15

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  • DOI: https://doi.org/10.1007/978-3-642-20042-7_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20041-0

  • Online ISBN: 978-3-642-20042-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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