Location-Based Service with Context Data for a Restaurant Recommendation (original) (raw)

Abstract

Utilizing Global Positioning System (GPS) technology, it is possible to find and recommend restaurants for users operating mobile devices. For recommending restaurants, Personal Digital Assistants or cellular phones only consider the location of restaurants. However, a user’s background and environment information is assumed to be directly related to recommendation quality. In this paper, therefore, a recommender system using context information and a decision tree model for efficient recommendation is presented. This system considers location context, personal context, environment context, and user preference. Restaurant lists are obtained from location context, personal context, and environment context using the decision tree model. In addition, a weight value is used for reflecting user preferences. Finally, the system recommends appropriate restaurants to the mobile user. For this experiment, performance was verified using measurements such as _k_-fold cross-validation and Mean Absolute Error. As a result, the proposed system obtained an improvement in recommendation performance.

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Author information

Authors and Affiliations

  1. Intelligent E-Commerce Systems Laboratory, Department of Computer Science & Information Engineering, Inha University,
    Bae-Hee Lee, Heung-Nam Kim & Jin-Guk Jung
  2. School of Computer Science & Engineering, Inha University, 253 Yonghyun-dong, Incheon, 402-751, Korea
    Geun-Sik Jo

Authors

  1. Bae-Hee Lee
  2. Heung-Nam Kim
  3. Jin-Guk Jung
  4. Geun-Sik Jo

Editor information

Editors and Affiliations

  1. School of Computing, National University of Singapore,
    Stéphane Bressan
  2. University of Linz, Altenbergerstraße 69, 4040, Linz, Austria
    Josef Küng & Roland Wagner &

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© 2006 Springer-Verlag Berlin Heidelberg

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Lee, BH., Kim, HN., Jung, JG., Jo, GS. (2006). Location-Based Service with Context Data for a Restaurant Recommendation. In: Bressan, S., Küng, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2006. Lecture Notes in Computer Science, vol 4080. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11827405\_42

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