PGT: Measuring Mobility Relationship using Personal, Global and Temporal Factors

被引:59
|
作者
Wang, Hongjian [1 ]
Li, Zhenhui [1 ]
Lee, Wang-Chien [2 ]
机构
[1] Penn State Univ, Coll Informat Sci & Technol, University Pk, PA 16802 USA
[2] Penn State Univ, Dept Comp Sci & Engn, University Pk, PA 16802 USA
关键词
mobility; relationship strength; spatiotemporal; social computing;
D O I
10.1109/ICDM.2014.111
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Rich location data of mobile users collected from smartphones and location-based social networking services enable us to measure the mobility relationship strength based on their interactions in the physical world. A commonly-used measure for such relationship is the frequency of meeting events (i.e., co-locate at the same time). That is, the more frequently two persons meet, the stronger their mobility relationship is. However, we argue that not all the meeting events are equally important in measuring the mobility relationship and propose to consider personal and global factors to differentiate meeting events. Personal factor models the probability for an individual user to visit a certain location; whereas the global factor models the popularity of a location based on the behavior of general public. In addition, we introduce the temporal factor to further consider the time gaps between meeting events. Accordingly, we propose a unified framework, called PGT, that considers personal, global, and temporal factors to measure the strength of the relationship between two given mobile users. Extensive experiments on real datasets validate our ideas and show that our method significantly outperforms the state-of-the-art methods.
引用
收藏
页码:570 / 579
页数:10
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