- Volume 16 Issue 4
DOI QR Code
Friend Recommendation Scheme Using Moving Patterns of Mobile Users in Social Networks
소셜 네트워크에서 모바일 사용자 이동 패턴을 이용한 친구 추천 기법
- Received : 2015.11.16
- Accepted : 2016.01.19
- Published : 2016.04.28
With the development of information technologies and the wide spread of smart devices, the number of users of social network services has increased exponentially. Studies that identify user preferences and recommend similar users in these social network services have been actively done. In this paper, we propose a new scheme to recommend social network friends with similar preferences through the moving pattern analysis of mobile users. The proposed scheme removes the meaningless trajectories via companions, short time trajectories, and repeated trajectories to determine the correct user preference. The proposed scheme calculates user similarity using the meaningful trajectories and recommends users with similar preferences as friends. It is shown through performance evaluation that the proposed scheme outperforms the existing schemes.
Friend Recommendation;Moving Pattern;Social Network;Mobile Network
- Z. Yu and X. Xing, "Learning Location Correlation from GPS Trajectories," Proc. International Conference on Mobile Data Management, pp. 27-32, 2010.
- T. Dong, N. Cheng, and Y. J. Wu, "A study of the social networking website service in digital content industries: The Facebook case in Taiwan," Computers in Human Behavior, Vol. 30, pp. 708-714, 2014. https://doi.org/10.1016/j.chb.2013.07.037
- Y. Zheng, X. Xie, and W. Ma, "GeoLife: A Collaborative Social Networking Service among User, Location and Trajectory," IEEE Data Engineering Bulletin, Vol. 33, No. 2, pp. 32-39, 2010.
- H. Kwak, C. Lee, H. Park, and S. Moon, "What is Twitter, a social network or a news media?," Proc. International conference on World Wide Web, pp. 591-600, 2010.
- B. Berjani and T. Strufe, "A Recommendation System for Spots in Location-based Online Social Networks," Proc. Workshop on Social Network System, pp. 4, 2011.
- K. W. Leung, D. L. Lee, and W. Lee, "CLR: a collaborative location recommendation framework based on co-clustering," Proc. International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 305-314, 2011.
- J. H. Cha, J. G. Kim, J. T. Lim, K. S. Bok, and J. S. Yoo, "A Location Recommendation Scheme Considering Companions and Distance in Mobile Social Networks," Proc. International Conference on Convergence Content, pp. 243-244, 2013.
- E. Tiakas, A. N. Papadopoulos, A. Nanopoulos, Y. Manolopoulos, D. Stojanovic, and S. Djordjevic-Kajan, "Trajectory Similarity Search in Spatial Networks," Proc. International Database Engineering and Applications Symposium, pp. 185-192, 2006.
- G. Chen, B. Chen, and Y. Yu, "Mining Frequent Trajectory Patterns from GPS Tracks," Proc. International Conference on Computational Intelligence and Software Engineering, pp. 1-6, 2010.
- Z. Li, M. Ji, J. Lee, L. Tang, Y. Yu, J. Han, and R. Kays, "MoveMine: Mining Moving Object Databases," Proc. ACM SIGMOD International Conference on Management of data, pp. 1203-1206, 2010.
- G. Roh, J. Roh, S. Hwang, and B. Yi, "Supporting Pattern Matching Queries over Trajectories on Road Networks," IEEE Transactions on Knowledge and Data Engineering, Vol. 23, No. 11, pp. 1753-1758, 2011. https://doi.org/10.1109/TKDE.2010.189
- X. Li, J. Han, J. Lee, and H. Gonzalez, "Traffic Density-Based Discovery of Hot Routes in Road Networks," Proc. International Symposium on Advances in Spatial and Temporal Databases, pp. 441-459, 2007.
- N. Pelekis, I. Kopanakis, E. E. Kotsifakos, E. Frentzos, and Y. Theodoridis, "Clustering Trajectories of Moving Objects in an Uncertain World," Proc. International Conference on Data Mining, pp. 417-427, 2009.
- A. Kharrat, K. Zeitouni, I. Sandu-Popa, and S. Faiz, "Characterizing Traffic Density and Its Evolution through Moving Object Trajectories," Proc. the International Conference on Knowledge Discovery and Information Retrieval, pp. 319-322, 2009.
- H. M. O. Mokhtar, O. Ossama, and M. E. Sharkawi, "A Time Parameterized Technique for Clustering Moving Object Trajectories," International Journal of Data Mining and Knowledge Management Process, Vol. 1, No. 1, pp. 14-30, 2011. https://doi.org/10.5121/ijdkp.2011.1302
- R. Li, S. Wang and K. Chen-Chuan, "Multiple Location Profiling for Users and Relationships from Social Network and Content," Proc. VLDB Endowment, Vol. 5, No. 11, pp. 1603-1614, 2012.
- M. J. Lee and C. Chung, "User Similarity Calculation Based on the Location for Social Network Services," Proc. International Conference on Database Systems for Advanced Applications, pp. 38-52, 2011.
- X. Xiao, Y. Zheng, Q. Luo, and X. Xie, "Inferring social ties between users with human location history," Journal of Ambient Intelligence and Humanized Computing, Vol. 5, No. 1, pp. 3-19, 2014. https://doi.org/10.1007/s12652-012-0117-z
- 이충희, 박용훈, 임종태, 복경수, 유재수, "모바일 소셜 네트워크를 위한 사용자의 선호도 및 이동 패턴을 이용한 친구 추천," 정보과학회논문지:데이타베이스, 제40권, 제1호, pp. 79-87, 2013.
- 노연우, 김대윤, 한지은, 육미선, 임종태, 복경수, 유재수, "소셜 네트워크에서 사용자의 영향력을 고려한 핫 토픽 예측 기법," 한국콘텐츠학회논문지, 제15권, 제8호, pp. 24-36, 2015.
- 양희태, 차재홍, 안민제, 임종태, 이하, 복경수, 유재수, "동적 사용자 프로필 및 협업 필터링을 이용한 소셜 네트워크 그룹 추천," 한국콘텐츠학회논문지, 제13권, 제11호, pp. 11-20, 2013.
- J. Leskovec, A. Rajaraman, and J. Ullman, "Mining of Massive Datasets," Cambridge, pp. 1-17, 2014.
Supported by : 정보통신기술진흥센터, 한국연구재단, 한국에너지기술평가원(KETEP)