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P-Trie Tree: A Novel Tree Structure for Storing Polysemantic Data

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Natural Language Processing and Chinese Computing (NLPCC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9362))

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Abstract

Trie tree, is an ordered tree data structure that is used to store a dynamic set or associative array where the keys are usually strings. It makes the search and update of words more efficient and is widely used in the construction of English dictionary for the storage of English vocabulary. Within the application of big data, efficiency determines the availability and usability of a system. In this paper, I introduce p-trie tree-a novel trie tree structure which can be used for polysemantic data which are not limited to English strings. I apply p-trie to the storage of Japanese vocabulary and evaluate the performance through experiments.

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References

  1. http://mecab.googlecode.com/svn/trunk/mecab/doc/index.html

  2. Jansson, J., Sadakane, K., Sung, W.-K.: Linked Dynamic Tries with Applications to LZ-Compression in Sublinear Time and Space. Algorithmica 71(4), 969–988 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  3. Leckey, K., Neininger, R., Szpankowski, W.: A Limit Theorem for Radix Sort and Tries with Markovian Input (2015). CoRR abs/1505.07321

    Google Scholar 

  4. Amano, S., Ogawa, M., Aizawa, K.: Frequency statistics of words used in Japanese food records of FoodLog. In: UbiComp Adjunct 2014, pp.547–552 (2014)

    Google Scholar 

  5. Akiyama, Y., Shibasaki, R.: A method for identifying japanese shop and company names by spatiotemporal cleaning of eccentrically located frequently appearing words. In: Adv. Artificial Intellegence (ADVAI 2012), pp. 562604:1–562604:18 (2012)

    Google Scholar 

  6. Noro, T., Tokuda, T.: Ranking words for building a japanese defining vocabulary. In: IJCNLP 2008, pp. 679–684 (2008)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Economic Engineering, Kyushu University, Fukuoka, 812-8581, Japan

    Xin Zhou

Authors
  1. Xin Zhou
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Correspondence to Xin Zhou .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Juanzi Li

  2. Rensselaer Polytechnic Institute, Troy, NY, USA

    Heng Ji

  3. Peking University, Beijing, China

    Dongyan Zhao

  4. Peking University, Beijing, China

    Yansong Feng

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© 2015 Springer International Publishing Switzerland

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Zhou, X. (2015). P-Trie Tree: A Novel Tree Structure for Storing Polysemantic Data. In: Li, J., Ji, H., Zhao, D., Feng, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2015. Lecture Notes in Computer Science(), vol 9362. Springer, Cham. https://doi.org/10.1007/978-3-319-25207-0_31

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  • DOI: https://doi.org/10.1007/978-3-319-25207-0_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25206-3

  • Online ISBN: 978-3-319-25207-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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