A smartphone user activity prediction framework utilizing partial repetitive and landmark behaviors

Proceedings - IEEE International Conference on Mobile Data Management

Volumn 1, Issue , 2014, Pages 205-210

  Dai, Peng ^a   Ho, Shen Shyang ^b  

^a UNIVERSITY OF TORONTO   (Canada)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Eigenbehavior; Landmark patterns; Mobilility Data; partial repetitive patterns; predictability; Principal Component Analysis; Sequential Prediction

Indexed keywords

INFORMATION MANAGEMENT; PRINCIPAL COMPONENT ANALYSIS; SMARTPHONES; VECTOR SPACES;

EIGENBEHAVIOR; LANDMARK PATTERNS; MOBILILITY DATA; PREDICTABILITY; REPETITIVE PATTERN; SEQUENTIAL PREDICTION;

FORECASTING;

EID: 84908011905     PISSN: 15516245     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MDM.2014.31     Document Type: Conference Paper

References (17)

1. M. Scriven, "An essential unpredictability in human behavior," Scientific Psychology: Principles and Approaches, pp. 411-425, 1965.
2. G. A. Cziko, "Unpredictability and indeterminism in human behavior: Arguments and implications for educational research," Educational Researcher, vol. 18, no. 3, pp. 17-25, 1989.
3. C. Song, Z. Qu, N. Blumm, and A.-L. Barabási, "Limits of predictability in human mobility," Science, vol. 327, no. 5968, pp. 1018-1021, 2010.
4. D. Wang, D. Pedreschi, C. Song, F. Giannotti, and A.-L. Barabási, "Human mobility, social ties, and link prediction," in KDD, C. Apté, J. Ghosh, and P. Smyth, Eds. ACM, 2011, pp. 1100-1108.
5. S. Rajagopal, N. Srinivasan, R. B. Narayan, and X. B. C. Petit, "Gps based predictive resource allocation in cellular networks," in 10th IEEE International Conference on Networks (ICON), 2002.
6. J. J. Pan, J. T. Kwok, Q. Yang, and Y. Chen, "Multidimensional vector regression for accurate and low-cost location estimation in pervasive computing," IEEE Transactions on Knowledge and Data Engineering, vol. 18, pp. 1181-1193, 2006.
7. T. H. N. Vu, K. H. Ryu, and N. Park, "A method for predicting future location of mobile user for location-based services system," Computers & Industrial Engineering, vol. 57, pp. 91-105, 2009.
8. W. Pan, N. Aharony, and A. Pentland, "Composite social network for predicting mobile apps installation," in AAAI, W. Burgard and D. Roth, Eds. AAAI Press, 2011.
9. N. Eagle and A. S. Pentland, "Eigenbehaviors: Identifying structure in routine," Behavioral Ecology and Sociobiology, vol. 63, pp. 1057-1066, 2009.
10. X. Xiao, Y. Zheng, Q. Luo, and X. Xie, "Inferring social ties between users with human location history," Journal of Ambient Intelligence and Humanized Computing, pp. 1-17, 2012.
11. P. Dai and S. S. Ho, "Predicting mobile call behavior via subspace methods," in International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP 2013), 2013.
12. W. H. Chai, H. Guo, and S.-S. Ho, "Robust prediction in nearly periodic time series using motifs," in International Conference on Neural Networks, 2014.
13. J. K. Laurila, D. Gatica-Perez, I. Aad, J. Blom, O. Bornet, T.-M.-T. Do, O. Dousse, J. Eberle, and M. Miettinen, "The mobile data challenge: Big data for mobile computing research," in Proc. on Mobile Data Challenge by Nokia Workshop in conjunction with Int. Conf. on Pervasive Computing, 2012.
14. N. Kiukkonen, J. Blom, O. Dousse, D. Gatica-Perez, and J. Laurila, "Towards rich mobile phone datasets: Lausanne data collection campaign," Proc. ICPS, Berlin, 2010.
15. B. Gold and N. Morgan, Speech and audio signal processing-processing and perception of speech and music. John Wiley and Sons, Inc, 2000.
16. J. A. Hartigan, Clustering algorithms. John Wiley & Sons, Inc., 1975.
17. B. Schölkopf, A. J. Smola, and K.-R. Müller, "Kernel principal component analysis," in ICANN, ser. Lecture Notes in Computer Science, W. Gerstner, A. Germond, M. Hasler, and J.-D. Nicoud, Eds., vol. 1327. Springer, 1997, pp. 583-588.