Location Recommendation System based on LBSNS

LBSNS 기반 장소 추천 시스템

  • Jung, Ku-Imm (Department of Strategy Marketing, SeeOn Inc.) ;
  • Ahn, Byung-Ik (Department of Strategy Marketing, SeeOn Inc.) ;
  • Kim, Jeong-Joon (Division of Computer Science & Engineering, Konkuk University) ;
  • Han, Ki-Joon (Division of Computer Science & Engineering, Konkuk University)
  • 정구임 ((주)씨온 전략마케팅팀) ;
  • 안병익 ((주)씨온 전략마케팅팀) ;
  • 김정준 (건국대학교 컴퓨터공학부) ;
  • 한기준 (건국대학교 컴퓨터공학부)
  • Received : 2014.04.04
  • Accepted : 2014.06.20
  • Published : 2014.06.28


In LBSNS(Location-based Social Network Service), users can share locations and communicate with others by using check-in data. The check-in data consists of POI name, category, coordinate and address of locations, nickname of users, evaluating grade of locations, related article/photo/video, and etc. If you analyze the check-in data from the location-based social network service in accordance with your situation, you can provide various customized services. Therefore, In this paper, we develop a location recommendation system based on LBSNS that can utilize the check-in data efficiently. This system analyzes the location category of the check-in data, determines the weighted value of it, and finds out the similarity between users by using the Pearson correlation coefficient. Also, it obtains the preference score of recommended locations by using the collaborated filtering algorithm and then, finds out the distance score by applying the Euclidean's algorithm to the recommended locations and the current users' locations. Finally, it recommends appropriate locations by applying the weighted value to the preference score and the distance score. In addition, this paper approved excellence of the proposed system throughout the experiment using real data.


LBSNS;Check-in Data Analysis;Location Recommendation;User Similarity


Supported by : 중소기업청


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