Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
권호 표지
DOI QR코드

DOI QR Code

The Development of Users' Interesting Points Analyses Method and POI Recommendation System for Indoor Location Based Services

실내 위치기반 서비스를 위한 사용자 관심지점 탐사 기법과 POI추천 시스템의 구현

  • Kim, Beoum-Su (Dept. of Computer & Information Engineering, Inha University) ;
  • Lee, Yeon (Dept. of Computer & Information Engineering, Inha University) ;
  • Kim, Gyeong-Bae (Dept. of Computer Education, Seowon University) ;
  • Bae, Hae-Young (Dept. of Computer & Information Engineering, Inha University)
  • 김범수 (인하대학교 컴퓨터정보공학과) ;
  • 이연 (인하대학교 컴퓨터정보공학과) ;
  • 김경배 (서원대학교 컴퓨터교육과) ;
  • 배해영 (인하대학교 컴퓨터정보공학과)
  • Received : 2012.02.23
  • Accepted : 2012.04.12
  • Published : 2012.05.31
Download PDF
⟨ Previous Next ⟩

Abstract

Recently, as location-determination of indoor users is available with the development of variety of localization techniques for indoor location-based service, diverse indoor location based services are proposed. Accordingly, it is necessary to develop individualized POI recommendation service for recommending most interested points of large-scale commercial spaces such as shopping malls and departments. For POI recommendation, it is necessary to study the method for exploring location which users are interested in location with considering user's mobility in large-scale commercial spaces. In this paper, we proposed POI recommendation system with the definition of users' as 'Stay point' in order to consider users' various interest locations. By using the proposed algorithm, we analysis users' Stay points, then mining the users' visiting pattern to finished the proposed. POI Recommendation System. The proposed system decreased data more dramatically than that of using user's entire mobility data and usage of memory.

최근 실내 위치기반서비스를 위한 다양한 측위 기술의 발전으로 실내에서도 사용자의 위치측정이 가능해짐에 따라 다양한 형태의 실내 위치기반 서비스가 개발되고 있다. 이에 쇼핑몰이나 백화점 등의 대규모 상업 공간 같은 복잡한 실내 공간에서 사용자에게 가장 적합한 위치나 매장을 추천하는 개인화된 POI 추천 시스템의 개발이 필요하게 되었다. POI 추천을 위해서는 사용자의 이동성과 대규모 상업공간의 공간성을 고려한 사용자 관심지점 탐사 기법의 연구가 필요하다. 이에 본 논문에서는 실내 위치기반 서비스의 POI 추천 시스템의 구현과 사용자들의 이동 데이터로부터 다양한 관심지점을 고려하기 위해 사용자가 일정 시간 동안 머무른 지점을 Stay point라 정의하고 실내공간에서 Stay point를 탐색하는 알고리즘을 제안하였다. 또한 제안된 알고리즘을 이용하여 탐색한 Stay point로부터 방문패턴을 탐사하여 POI 추천 시스템을 구현하였다. 구현된 시스템은 사용자의 모든 이동 로그를 이용한 패턴탐사보다 데이터양을 획기적으로 줄임으로써 빠른 패턴탐사와 메모리 사용량을 줄일 수 있었다.

Keywords

References

  1. Jae Kyeong Kim, Kyung Hee Chae, Min Yong Kim, "A Store Recommendation Procedure in Ubiquitous Market," Journal of Intelligence and Information Systems, Vol 13, No. 4, pp.45-63, Dec. 2007
  2. Jong-Hee Kim, Soon-Key Jung, "The Goods Recommendation System based on modified FP-Tree Algorithm" Journal of the Korea society of computer and information, pp.205-213, Jun. 2010.
  3. Jin Byeong Woon, Cho Young Sung, Ryu Keun Ho, "Personalized e-Commerce Recommendation System using RFM method and Association Rules" Journal of the Korea society of computer and information, pp.227-235, Sept. 2010.
  4. Vu. Thi Hong Nhan, Bum Ju Lee, Keun Ho Ryu, "Discovert of Frequent Sequence Pattern in Moving Object Databases," The KIPS Transactions:PartD, Vol 15D, No. 2, pp.163-170, Apr. 2008.
  5. Sonia Khetarpaul, Rashmi Chauhan, S K Gupta, L Venkata Subramaniam, Ullas Nambiar, "Mining GPS Data to Determine Interesting Locations," IIWeb '11 Proceedings of the 8th International Workshop on Information Integration on the Web: in conjunction with WWW 2011, No. 8, Mar. 2011.
  6. Quannan Li, Yu Zheng, Xing Xie, Yukun Chen, Wenyu Liu, Wei-Ying Ma , "Mining User Similarity Based on Location History," GIS '08 Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems, No. 34, Nov. 2008
  7. Young Hwan Choi, Sang Yong Lee, "Users' Moving Patterns Analysis for Personalized Product Recommendation in Offline Shopping Malls," Journal of Korean Institute of Intelligent Systems, Vol 16, No. 2, pp.185-190, Apr. 2006. https://doi.org/10.5391/JKIIS.2006.16.2.185
  8. Ji Woong Park, Dong Suk Hong, Dong Oh Kim, Ki Joon Han, "An Efficient Algorithm for Spatio-Temporal Moving Pattern Extraction," Journal of Korea Spatial Information System Society, Vol 8, No. 2, pp.1-124, Sept. 2006.
  9. Rakesh Agrawal, Ramakrishnan Srikant, "Mining Sequential Patterns," Proc. of the Int. Conf. on Data Engineering, Taipei, Taiwan, 1995.
  10. Jiwei Han and Micheline Kamber, "Data Mining Conceptions and Techniques, ELSEVIER Inc., pp.224-235 2006.
  11. Hyung Bong Lee, "An implementation and Performance Characteristics of the FP-tree Association Rules Mining Algorithm," Proceedings of the Korea Information Processing Society Conference, Vol 13, No. 2, pp.337-340, Nov. 2006.

Cited by

  1. 유사도검사 기법을 이용한 안전관리 개선시스템 연구 vol.9, pp.4, 2012, https://doi.org/10.15207/jkcs.2018.9.4.023