Predicting stay time of mobile users with contextual information

IEEE Transactions on Automation Science and Engineering

Volumn 10, Issue 4, 2013, Pages 1026-1036

  Liu, Sen ^a   Cao, Huanhuan ^b   Li, Lei ^a   Zhou, Mengchu ^c,d  

^a BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^b NOKIA RESEARCH CENTER   (United States)

^c NEW JERSEY INSTITUTE OF TECHNOLOGY   (United States)

^d Ministry of Education   (China)

Author keywords

Contextual information; mobile users; stay time prediction (STP)

Indexed keywords

CONTEXTUAL INFORMATION; EFFECTIVENESS AND EFFICIENCIES; LOCATION INFORMATION; MACHINE LEARNING MODELS; MOBILE SERVICE PROVIDERS; MOBILE USERS; PREDICTION ACCURACY; TIME PREDICTIONS;

MOBILE DEVICES;

FORECASTING;

EID: 84885471458     PISSN: 15455955     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASE.2013.2259480     Document Type: Article

References (33)

1. G. Adomavicius and A. Tuzhilin, Context-Aware Recommender Systems. New York, NY, USA: Springer, 2011.
2. T. Anagnostopoulos, C. Anagnostopoulos, and S. Hadjiefthymiades, "Mobility prediction based on machine learning," in Proc. 12th IEEE Int. Conf. Mobile Data Management(MDM2011), Los Alamitos, CA, USA, 2011, pp. 27-30.
3. T. Bao, H. Cao, E. Chen, J. Tian, and H. Xiong, "An unsupervised approach to modeling personalized contexts of mobile users," in Proc 10th IEEE Int. Conf. Data Mining (ICDM'10), Sydney, Australia, 2010, pp. 38-47.
4. R. B. Braga, A. Tahir, M. Bertolotto, and H. Martin, "Clustering user trajectories to find patterns for social interaction applications," in Web and Wireless Geographical Inform. Syst., 2012, pp. 82-97.
5. L. Breiman, J. H. Friedman, andR. A. E. A. Olshen, Classification and Regression Trees. Boca Raton, FL, USA: CRC Press, 1984.
6. F. Calabrese, G. Di Lorenzo, and C. Ratti, "Human mobility prediction based on individual and collective geographical preferences," in Proc. 13th IEEE Int. Conf. Intell. Transp. Syst. (ITSC'10), 2010, pp. 312-317.
7. H. Cao, T. Bao, Q. Yang, E. Chen, and J. Tian, "An effective approach for mining mobile user habits," in Proc. 19th ACM Conf. Inform. Knowl. Management (CIKM2010), Toronto, ON, Canada, 2010, pp. 1677-1680.
8. C. Chang and C. Lin, "LIBSVM: A library for support vector machines," ACMTrans. Intell. Syst. Technol., vol. 2, no. 27, pp. 1-27,Apr. 2011. [Online]. Available: http://www.csie.ntu.edu.tw/~cjlin/libsvm
9. I. C.-H. Lu and I. L.-C. Lu, "Robust location-aware activity recognition using wireless sensor network in an attentive home," IEEE Trans. Autom. Sci. Eng., vol. 6, no. 4, pp. 598-598, Oct. 2009.
10. C. Cortes and V. Vapnik, "Support-vector networks," Mach. Learn., vol. 20, no. 2, pp. 273-297, 1995.
11. S. Derksen and H. J.Keselman, "Backward, forward and stepwise automated subset selection algorithms:Frequency of obtaining authentic and noise variables," Br. J.Math. Statist. Psychology, pp. 265-282, 1992.
12. R. E. Fan, P. H. Chen, and C. J. Lin, "Working set selection using second order information for training SVM," J. Mach. Learn. Res., pp. 1889-1918, 2005.
13. E. Horvitz, P. Koch, C. M. Kadie, and A. Jacobs, "Coordinate: Probabilistic forecasting of presence and availability," in Proc. 18th Conf. Uncertainty Artifi. Intell. (UAI'02), 2002, pp. 224-233.
14. T. Jolliffe, Principal Component Analysis, 2nd ed. New York, NY, USA: Springer-Verlag, 2002.
15. J.-M. Kim, H. Baek, and Y.-T. Park, "Probabilistic graphical model based personal route prediction in mobile environment," Appl. Math. Inform. Sci., pp. 651-659, 2012.
16. J. Krumm and A. Brush, "Learning time-based presence probabilities," in Proc. 9th Int. Conf. Pervasive Computing (Pervasive'11), Jun. 2011, pp. 79-96.
17. X. Li, H. Cao, E. Chen, and J. Tian, "Learning to infer the status of heavy-duty sensors for energy-efficient context-sensing," ACM TIST, vol. 3, no. 2, pp. 35-35, 2012.
18. H.Ma, H. Cao, Q. Y. E.Chen, and J. Tian, "An unsupervised approach to modeling personalized contexts of mobile users," in Proc. 21th Int. Conf. World Wide Web (WWW2012), Lyon, France, 2012.
19. M. I. A. V. O.Wigstron, B. Lennartson, and C. Breitholtz, "High-level scheduling of energy optimal trajectories," IEEE Trans. Autom. Sci. Eng., vol. 10, no. 1, pp. 57-64, Jan. 2013.
20. J. R. Quinlan, C4.5: Programs for Machine Learning. SanMateo, CA, USA: Morgan Kaufmann, 1993.
21. D. Riboni and C. Bettini, "Cosar: Hybrid reasoning for context-aware activity recognition," in Personal and Ubiquitous Computing, 2011, pp. 271-289.
22. J. Scott, A. B. Brush, J. Krumm, B. Meyers, M. Hazas, S. Hodges, and N. Villar, "Preheat: Controlling home heating using occupancy prediction," in Proc. 13th ACM Int. Conf. Ubiquitous Computi. (Ubi- Comp'11), Sep. 2011, pp. 281-290.
23. D. Steinberg and P. Colla, "Cart-classification and regression trees," in Salford Systems, 1997, pp. 217-224.
24. U. Straccia, "Transportation planning with modified s-curve membership functions using an interactive fuzzy multi-bojective approach," in Appl. Soft Comput., 2011, pp. 2656-2663.
25. W.-M.Wu, F.-T. Cheng, T.-H. Lin,D.-L. Zeng, and J.-F. Chen, "Selection schemes of dual virtualmetrology outputs for enhancing prediction accuracy," IEEE Trans. Autom. Sci. Eng., vol. 8, no. 2, pp. 311-318, Apr. 2011.
26. M.-I. W.-H. Liau, C.-L. Wu, and I. L.-C. Fu, "Inhabitants tracking system in a cluttered home environment via floor load sensors," IEEE Trans. Autom. Sci. Eng., vol. 5, no. 1, pp. 10-10, Jan. 2008.
27. H. G. Williamus, Conometric Analysis 5th. Englewood Cliffs, USA: Prentice-Hall, 2002.
28. W.Woerndl, J. Huebner, R. Bader, and D. Gallego-Vico, "A model for proactivity in mobile, context-aware recommender systems," in Proc. 5th ACM Conf. Recommender Syst., 2011, pp. 273-276.
29. J. J.-C. Ying,W.-C. Lee, T.-C. Weng, and V. S. Tseng, "Semantic trajectory mining for location prediction," in Proc. 19th ACM SIGSPATIAL Int. Conf. Advances Geographic Inform. Syst. (GIS'11), 2011, pp. 34-43.
30. M. I. Y. Yu, T.-M. Choi, and C.-L. Hui, "An intelligent quick prediction algorithm with applications in industrial control and loading problems," IEEE Trans. Autom. Sci. Eng., vol. 9, no. 2, pp. 276-276, Apr. 2012.
31. Y. Zheng, X. Xie, andW.-Y. Ma, "Geolife: A collaborative social networking service among use, location and trajectory," IEEE Data Eng. Bull., 2010.
32. Y. Tang, M. C. Zhou, and M. Gao, "Fuzzy-Petri-net based disassembly planning considering human factors," IEEE Trans. Syst., Man, Cybern.: Part A, vol. 36, no. 4, pp. 718-726, Jul. 2006.
33. K. Venkatesh, M. C. Zhou, and R. Caudill, "Design of artificial neural network for tool wear monitoring," J. Intell. Manuf., vol. 8, no. 3, pp. 215-226, 1997. (Pubitemid 127506239)