Abstract
With the popularity of mobile phones and mobile applications, it becomes possible to collect large-scale mobility data and do research on human mobility. Among these research, relationship mining from location information is a hot topic which has plenty of applications including marketing applications, social studies and even terrorist discovery. This paper focuses on measuring the relationship strength of user pairs according to their meeting events. A novel method using multiple factors extracted from merged meeting events is proposed for measuring relationship. Firstly, meeting events are merged and each merged meeting event is represented by several features, from which multiple factors can be drawn. Specifically, the duration factor and the diameter factor are proposed for measuring relationship on the basis of merged meeting events. Finally, a model synthesizing multiple factors (including location entropy factor, location personal factor, temporal factor, duration factor and diameter factor) is proposed to quantify the relationship between users in an unsupervised way. Experimental results on three different real datasets demonstrate that our method performs significantly more favorable than existing methods on the effectiveness.
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Acknowledgements
This work is supported by National Natural Science Foundation of China (No. 61361166009).
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Chen, Z., Wang, K., Yang, Z. (2017). Relationship Measurement Using Multiple Factors Extracted from Merged Meeting Events. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10638. Springer, Cham. https://doi.org/10.1007/978-3-319-70139-4_34
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DOI: https://doi.org/10.1007/978-3-319-70139-4_34
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