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Best Recommendation Using Topic Map for On-Line Shopping System

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Convergence and Hybrid Information Technology (ICHIT 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 206))

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Abstract

Topic map is generally used to recommend shopping list as analyze a user preference in internet shopping mall. It is useful method to propose the preference that is related access rate and selecting time of production. In this research, we apply this method to analyze the user characteristics in on-line shopping system. To analyze user preference, we used the topic preference vector that is able to calculate the access rate with visiting time and production selection. And we designed and developed the path of on-line shopping site. It will help to navigate the shopping by recommendation of on-line shopping list.

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Author information

Authors and Affiliations

  1. Humanitas College of Kyunghee University, Hoegi-dong, Seoul, 130-701, Korea

    HwaYoung Jeong

  2. Dept. of Information and Communication, Kyunghee Cyber University, Hoegi-dong, Seoul, 130-701, Korea

    BongHwa Hong

Authors
  1. HwaYoung Jeong
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  2. BongHwa Hong
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Editor information

Editors and Affiliations

  1. 90301, 3F, Computer Engineering Department, Hannam University, 70 Hannamro, Daedeuk-gu, Daejeon, Korea

    Geuk Lee

  2. QinetiQ Company Fellow, Howard Science Limited, 24 Sunrise, WR14 2NJ, Malvern, United Kingdom

    Daniel Howard

  3. Institute of Mathematics, University of Warsaw, ul. Banacha 2, 02-097, Warsaw, Poland

    Dominik Ślęzak

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© 2011 Springer-Verlag Berlin Heidelberg

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Jeong, H., Hong, B. (2011). Best Recommendation Using Topic Map for On-Line Shopping System. In: Lee, G., Howard, D., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2011. Communications in Computer and Information Science, vol 206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24106-2_70

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  • DOI: https://doi.org/10.1007/978-3-642-24106-2_70

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24105-5

  • Online ISBN: 978-3-642-24106-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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