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Mobile Information Systems
Volume 2017, Article ID 7871502, 9 pages
Research Article

Recommending Locations Based on Users’ Periodic Behaviors

Department of Computer Science and Technology, Tongji University, Shanghai, China

Correspondence should be addressed to Zhijun Ding; nc.ude.ijgnot@jzgnid

Received 23 September 2016; Revised 11 December 2016; Accepted 22 December 2016; Published 21 February 2017

Academic Editor: Qingchen Zhang

Copyright © 2017 Bing Xu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The research of location recommendation system is an important topic in the field of LBSN (Location-Based Social Network). Recently, more and more researchers began focusing on researching how to recommend locations based on user’s life behavior. In this paper, we proposed a new model recommending locations based on user’s periodic behaviors. In view of multiple periodic behaviors existing in time series, an algorithm which can mine all periods in time series is proposed in this paper. Based on the periodic behaviors, we recommend locations using item-based collaborative filtering algorithm. In this paper, we will also introduce our recommendation system which can collect users’ GPS trajectory, mine user’s multiple periods, and recommend locations based user’s periodic behavior.