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Implementing a Chinese Character Browser Using a Topography-Preserving Map

  • Conference paper
Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3973))

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Abstract

The Chinese Character Browser is a user interface designed for the search and exploration of a database of Chinese characters, Chinese pronunciations (pinyin), and English definitions. The browser uses a technology based upon Kohonen’s self-organizing map to map the 10-dimensional feature vector describing each Chinese character onto a discrete two-dimensional grid, which forms the foundation for the browser. The Chinese Character Browser was designed to demonstrate the importance not only of topology preservation, but topography preservation in such mappings. In brief, to the extent that a mapping is topography-preserving, the structure of the output map grid can reflect the structure of the original data at several levels of granularity simultaneously, allowing the assumption of a hierarchical organization in the output map that corresponds to the structure of the input data set. This can significantly speed up search as well as make the mapping more useful for a variety of applications.

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References

  1. Breen, J.: KANJIDIC Documentation (November 2005) . Unpublished, Available at, accessed, http://www.csse.monash.edu.au/~jwb/kanjidic.html

  2. Halpern, J.: NTC’s New Japanese-English Character Dictionary. National Textbook Co., Lincolnwood, Lincolnwood, Illinois (1993)

    Google Scholar 

  3. Kirk, J.S.: Algorithms to Improve Topography Preservation in Self-Organizing Maps. Ph.D. dissertation, University of Louisville (2003)

    Google Scholar 

  4. Kirk, J.S., Zurada, J.M.: An Evolutionary Method of Training Topography-Preserving Maps. In: Proceedings of the 2001 INNS-IEEE International Joint Conference on Neural Networks, Washington, D.C, July 14-19, pp. 2230–2234 (2001)

    Google Scholar 

  5. Kirk, J.S., Zurada, J.M.: Motivation for a Genetically-Trained Topography-Preserving Map. In: Proceedings of the 2002 International Joint Conference on Neural Networks, Honolulu, HI, May 12-17, pp. 394–399 (2002)

    Google Scholar 

  6. Kirk, J.S., Zurada, J.M.: Topography-Enhanced BMU Search in Self-Organizing Maps. In: Yin, F.-L., Wang, J., Guo, C. (eds.) ISNN 2004. LNCS, vol. 3174, pp. 695–700. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  7. Kohonen, T.: Self-Organizing Maps, 3rd edn. Springer, Berlin (2001)

    MATH  Google Scholar 

  8. Kohonen, T., Kaski, S., Lagus, K., Salojärvi, J., Honkela, J., Paatero, V., Saarela, A.: Self Organization of a Massive Document Collection. IEEE Trans. Neural Networks 11(3), 574–585 (2000)

    Article  Google Scholar 

  9. Koskela, M., Laaksonen, J., Laakso, S., Oja, E.: The PicSOM Retrieval System: Description and Evaluations. In: Eakins, J.P., Enser, P.G.B. (eds.) Proceedings of Challenge of Image Retrieval, Brighton, UK (2000)

    Google Scholar 

  10. Lagus, K., Kaski, S., Kohonen, T.: Mining Massive Document Collections by the WEBSOM Method. Information Sciences 163(1-3), 135–156 (2004)

    Article  Google Scholar 

  11. Oja, E., Laaksonen, J., Koskela, M., Brandt, S.: Self-Organizing Maps for Content-Based Image Database Retrieval. In: Oja, E., Kaski, S. (eds.) Kohonen Maps, pp. 349–362. Elsevier, Amsterdam (1999)

    Chapter  Google Scholar 

  12. Su, M.C., Chang, H.T.: Fast Self-Organizing Feature Map Algorithm. IEEE Trans. Neural Networks 11(3), 721–733 (2000)

    Article  Google Scholar 

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© 2006 Springer-Verlag Berlin Heidelberg

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Kirk, J.S. (2006). Implementing a Chinese Character Browser Using a Topography-Preserving Map. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_170

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  • DOI: https://doi.org/10.1007/11760191_170

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34482-7

  • Online ISBN: 978-3-540-34483-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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