Open Access
| Issue |
ITM Web Conf.
Volume 11, 2017
2017 International Conference on Information Science and Technology (IST 2017)
|
|
|---|---|---|
| Article Number | 03002 | |
| Number of page(s) | 9 | |
| Section | Session III: Network and Communication | |
| DOI | https://doi.org/10.1051/itmconf/20171103002 | |
| Published online | 23 May 2017 | |
- T.F. Bao. A Study On Context Recognition and Mining of Mobile User data. University of Science and Technology of China(2012). [Google Scholar]
- C. Song, Z. Qu, N. Blumm, et al. Limits of Predictability in Human Mobility. Science, 327(5968), 1018–1021(2010). [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
- X.F. Zhu. Research on Rapid Mining Algorithm for Massive Data. Nanjing University of Posts and Telecommunications(2012). [Google Scholar]
- Z.A. Dong, X.Q. Lu. User Behaviour Analyses Based on Baidu Search Logs. Computer Applications and Software, 30(7), 18–20(2013). [Google Scholar]
- Z.G. Z, C.Q. J, X.L. Wang, A.Y. Zhou. etc. Discovering Import Locations from Massiveand Low-Quality Cell Phone Trajectory Data. Journal of Software, 27(7), 1–14(2016). [Google Scholar]
- Y.X. Kong, C.Q. Jin, X.L. Wang. etc. Population Flow Analysis Based on Cellphone Trajectory Data. Journal of Computer Applications, 36 (1), 44–51(2016). [Google Scholar]
- J. Chen, B. Hu, X.Q. Z, Y. Yang. Personal Profile Mining Based on Mobile Phone Location Data. Geomatics and Information Science of Wuhan University, 39(6), 734–738(2014). [Google Scholar]
- S.F. Gong, W.L. Chen, P.T. Jia. Surver on Algorithms of Community Detection. Application Research of Computers, 30(11), 3216–3227(2013). [Google Scholar]
- T. Bao, Z.G. Zhang, C.Q. Jin. An Urban Population Flow Analysis System Based on Mobile Big Data[J]. Journal of East China Normal University(Nature Science), 9(5), 162–170(2015). [Google Scholar]
- Z.C. An. Mining User Mobility Behavior Based on Base Station. Harbin Institute of Technology(2011). [Google Scholar]
- N. X, L. Y, J.X. Hu. Identifying Home-Work LocationsFromShort-Term,Large-Scale, and Regularly Sampled Mobile Phone Tracking Data. Geomatics and Information Science of Wuhan University,39(6), 750–755(2014). [Google Scholar]
- J. Shen, L. Z, J.W. Yang, R. Li. Archical Clustering Algorithm Based onPartion. Computer Engineering and Applications, 43(31), 175–177(2007). [Google Scholar]
- Y. Miu. The Analysis of Data Based on TheHierarchical Clustering. Anhui University (2013). [Google Scholar]
- H. Ying, K.J. Xia, Data preprocessing method based on user characteristic of interests for web log mining. Proceedings-2014 4th International Conference on Instrumentation and Measurement, Computer, Communication and Control, 867–872(2014). [Google Scholar]
- Montoliu R, GaticaPerez D. Discovering human places of interest from multimodalmobile phone data. Proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia. ACM, 12(2010). [Google Scholar]
- Blumenstock J E. Using mobile phone data to measure the ties between nations. Proceedings of the 2011IConference. ACM, 195–202(2011). [Google Scholar]
- Park M, Lee T. Understanding science and technology information users through Iransaction loganalysis. LibraryHi Tech, 31(1), 123–140(2013). [CrossRef] [MathSciNet] [Google Scholar]
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