Contextual conditional models for smartphone-based human mobility prediction

UbiComp'12 - Proceedings of the 2012 ACM Conference on Ubiquitous Computing

Volumn , Issue , 2012, Pages 163-172

  Do, Trinh Minh Tri ^a   Gatica Perez, Daniel ^a  

^a IDIAP RESEARCH INSTITUTE   (Switzerland)

Author keywords

Mobile context; Prediction; Smartphone; User mobility

Indexed keywords

CONDITIONAL MODELS; CONTEXT DEPENDENT; CONTEXTUAL VARIABLES; ENSEMBLE METHODS; HUMAN BEHAVIORS; HUMAN MOBILITY; MOBILE CONTEXT; MOBILITY PATTERN; MULTIPLE MODELS; ONLINE PREDICTION; PROBABILISTIC FRAMEWORK; USER MOBILITY;

FORECASTING; SIGNAL ENCODING; UBIQUITOUS COMPUTING;

SMARTPHONES;

EID: 84867447757     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2370216.2370242     Document Type: Conference Paper

References (25)

1. R. Bajaj, S. L. Ranaweera, and D. P. Agrawal. GPS: location-tracking technology. Computer, 35(4):92-94, 2002.
2. A. T. Campbell, S. B. Eisenman, N. D. Lane, E. Miluzzo, and R. A. Peterson. People-centric urban sensing. In Proc. WICON, 2006.
3. O. Chapelle and S. S. Keerthi. Efficient algorithms for ranking with svms. Inf. Retr., 13:201-215, June 2010.
4. E. Cho, S. A. Myers, and J. Leskovec. Friendship and mobility: user movement in location-based social networks. In Proc. KDD, pages 1082-1090, 2011.
5. T.-M.-T. Do and D. Gatica-Perez. Groupus: Smartphone proximity data and human interaction type mining. In Proc. ISWC, June 2011.
6. N. Eagle and A. (Sandy) Pentland. Reality mining: sensing complex social systems. Personal Ubiquitous Comput., 10(4):255-268, 2006.
7. M. C. Gonzalez, C. A. Hidalgo, and A.-L. Barabasi. Understanding individual human mobility patterns. Nature, 453(7196):779-782, June 2008.
8. T. Heskes. Selecting weighting factors in logarithmic opinion pools. Proc. NIPS, pages 266-272, 1998.
9. J. Hightower, S. Consolvo, A. LaMarca, I. Smith, and J. Hughes. Learning and recognizing the places we go. In Proc. UbiComp, pages 159-176. 2005.
10. J. H. Kang, W. Welbourne, B. Stewart, and G. Borriello. Extracting places from traces of locations. Proc. WMASH, 9(3):110-118, 2004.
11. M. Kim, D. Kotz, and S. Kim. Extracting a mobility model from real user traces. In Proc. INFOCOM, 2006.
12. J. Krumm and A. J. B. Brush. Learning time-based presence probabilities. In Proc. Pervasive, 2011.
13. J. Krumm and E. Horvitz. Predestination: Inferring destinations from partial trajectories. In Proc. Ubicomp, pages 243-260, 2006.
14. H. J. Kushner and G. Yin. Stochastic Approximation Algorithms and Applications. Springer Verlag, 1997.
15. T. Liu, P. Bahl, and I. Chlamtac. Mobility modeling, location tracking, and trajectory prediction in wireless ATM networks. Selected Areas in Communications, 16(6):922-936, 1998.
16. A. Monreale, F. Pinelli, R. Trasarti, and F. Giannotti. Wherenext: a location predictor on trajectory pattern mining. In Proc. KDD, pages 637-646, 2009.
17. P. Nurmi and S. Bhattacharya. Identifying meaningful places: The non-parametric way. In Proc .Pervasive Computing, 2008.
18. S. Patel, J. Kientz, G. Hayes, S. Bhat, and G. Abowd. Farther than you may think: An empirical investigation of the proximity of users to their mobile phones. In Proc. Ubicomp, pages 123-140, 2006.
19. A. Peddemors, H. Eertink, and I. Niemegeers. Predicting mobility events on personal devices. Pervasive Mob. Comput., 6:401-423, August 2010.
20. M. Raento, A. Oulasvirta, R. Petit, and H. Toivonen. Contextphone: A prototyping platform for context-aware mobile applications. IEEE Pervasive Computing, 4(2):51-59, 2005.
21. S. Scellato, M. Musolesi, C. Mascolo, V. Latora, and A. T. Campbell. Nextplace: a spatio-temporal prediction framework for pervasive systems. In Proc. Pervasive, pages 152-169, 2011.
22. C. Song, Z. Qu, N. Blumm, and A.-L. Barabsi. Limits of predictability in human mobility. Science, 327(5968):1018-1021, 2010.
23. L. Song, D. Kotz, R. Jain, and X. He. Evaluating next-cell predictors with extensive wi-fi mobility data. In IEEE Transactions on Mobile Computing, pages 1414-1424, 2004.
24. L. Vu, Q. Do, and K. Nahrstedt. Jyotish: A novel framework for constructing predictive model of people movement from joint wifi/bluetooth trace. In PerCom, pages 54-62, 2011.
25. V. W. Zheng, Y. Zheng, X. Xie, and Q. Yang. Collaborative location and activity recommendations with gps history data. In Proc. WWW. ACM, 2010.