DocumentCode :
244983
Title :
PGT: Measuring Mobility Relationship Using Personal, Global and Temporal Factors
Author :
Hongjian Wang ; Zhenhui Li ; Wang-Chien Lee
fYear :
2014
fDate :
14-17 Dec. 2014
Firstpage :
570
Lastpage :
579
Abstract :
Rich location data of mobile users collected from smart phones 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.
Keywords :
mobile computing; probability; smart phones; social networking (online); PGT; general public behavior; location-based social networking services; meeting event frequency; mobile user location data collection; mobility relationship strength measurement; personal-global-and-temporal factors; physical world; probability; smart phones; time gaps; unified framework; Conferences; Data mining; mobility; relationship strength; social computing; spatiotemporal;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining (ICDM), 2014 IEEE International Conference on
Conference_Location :
Shenzhen
ISSN :
1550-4786
Print_ISBN :
978-1-4799-4303-6
Type :
conf
DOI :
10.1109/ICDM.2014.111
Filename :
7023374
Link To Document :
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