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The Study of Address Tree Coding Based on the Maximum Matching Algorithm in Courier Business

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E-business Technology and Strategy (CETS 2010)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 113))

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Abstract

As an important component of EMS monitoring system, address is different from user name with great uncertainty because there are many ways to represent it. Therefore, address standardization is a difficult task. Address tree coding has been trying to resolve that issue for many years. Zip code, as its most widely used algorithm, can only subdivide the address down to a designated post office, not the recipients’ address. This problem needs artificial identification method to be accurately delivered. This paper puts forward a new encoding algorithm of the address tree - the maximum matching algorithm to solve the problem. This algorithm combines the characteristics of the address tree and the best matching theory, and brings in the associated layers of tree nodes to improve the matching efficiency. Taking the variability of address into account, the thesaurus of address tree should be updated timely by increasing new nodes automatically through intelligent tools.

This research is partially supported by National High-tech R&D Program of China (863 Program: 2007AA06Z111), JingGang Star Talents Training Plan of Jiangxi Province, China.

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Author information

Authors and Affiliations

  1. Engineering Research Center of Nuclear Technology Application (East China Institute of Technology), Ministry of Education, 330013, Nanchang, Jiangxi, China

    Shumin Zhou & Bin Tang

  2. School of Information Engineering, East China Institute of Technology, 344000, Fuzhou, Jiangxi, China

    Wen Li

Authors
  1. Shumin Zhou
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  2. Bin Tang
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  3. Wen Li
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Editor information

Editors and Affiliations

  1. Queen’s University, 99 University Avenue, K7L 3N6, Kingston, Ontario, Canada

    Marzia Zaman

  2. Royal Military College of Canada, 13 General Crerar Cres, K7K 7B4, Kingston, ON, Canada

    Yawei Liang

  3. Université du Québec en Outaouais, 283 boul. Alexandre-Taché, C.P. 1250, J8X 3X7, Gatineau, Québec, Canada

    Sohail M Siddiqui

  4. CeBA Canada, 1107-2720 Queensview Drive, K2B 1A5, Ottawa, ON, Canada

    Tim Wang

  5. Sprott School of Business, Carleton University, 1125 Colonel By Drive, K1S 5B6, Ottawa, Ontario, Canada

    Vincent Liu

  6. University of Toronto, 172 St. George Street, M5R 0A3, Toronto, Canada

    Ceecee Lu

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© 2010 Springer-Verlag Berlin Heidelberg

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Zhou, S., Tang, B., Li, W. (2010). The Study of Address Tree Coding Based on the Maximum Matching Algorithm in Courier Business. In: Zaman, M., Liang, Y., Siddiqui, S.M., Wang, T., Liu, V., Lu, C. (eds) E-business Technology and Strategy. CETS 2010. Communications in Computer and Information Science, vol 113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16397-5_3

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  • DOI: https://doi.org/10.1007/978-3-642-16397-5_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16396-8

  • Online ISBN: 978-3-642-16397-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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