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Location-Based Service with Context Data for a Restaurant Recommendation

  • Bae-Hee Lee
  • Heung-Nam Kim
  • Jin-Guk Jung
  • Geun-Sik Jo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4080)

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.

Keywords

Global Position System Recommender System User Preference User Profile Environment Context 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bae-Hee Lee
    • 1
  • Heung-Nam Kim
    • 1
  • Jin-Guk Jung
    • 1
  • Geun-Sik Jo
    • 2
  1. 1.Intelligent E-Commerce Systems Laboratory, Department of Computer Science & Information EngineeringInha University 
  2. 2.School of Computer Science & EngineeringInha UniversityIncheonKorea

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