Study of LZ-based location prediction and its application to transportation recommender systems

Sensors (Switzerland)

Volumn 12, Issue 6, 2012, Pages 7496-7517

  Rodriguez Carrion, Alicia ^a   Garcia Rubio, Carlos ^a   Campo, Celeste ^a   Cortés Martín, Alberto ^a   Garcia Lozano, Estrella ^a   Noriega Vivas, Patricia ^a  

^a UNIVERSIDAD CARLOS III DE MADRID   (Spain)

Author keywords

Active LeZi; Ambient intelligence; GSM based location; LeZi Update; LZ; Prediction; Recommender system; Ubiquitous computing

Indexed keywords

EID: 84863218055     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s120607496     Document Type: Article

References (32)

1. Cook, D.J.; Augusto, J.C.; Jakkula, V.R. Ambient intelligence: Technologies, applications, and opportunities. Pervasive Mobile Comput. 2009, 5, 277-298.
2. José, R.; Rodrigues, H.; Otero, N. Ambient intelligence: Beyond the inspiring vision. J. Univ. Comput. Sci. 2010, 16, 1480-1499.
3. Weber, W.; Rabaey, J.M.; Aarts, E.H.L. Ambient Intelligence; Springer-Verlag: Berlin, Germany, 2005.
4. Cai, Y. Mobile intelligence. J. Univ. Comput. Sci. 2010, 16, 1650-1665.
5. Abu-Ghazaleh, H.; Alfa, A.S. Application of mobility prediction in wireless networks using markov renewal theory. IEEE Trans. Veh. Technol. 2010, 59, 788-802.
6. Liang, B.; Haas, Z.J. Predictive distance-based mobility management for multidimensional PCS networks. IEEE/ACM Trans. Netw. 2003, 11, 718-732.
7. Bhattacharya, A.; Das, S.K. LeZi-update: An information-theoretic framework for personal mobility tracking in PCS networks. ACM/Kluwer Wirel. Netw. J. 2002, 8, 121-135.
8. Ziv, J.; Lempel, A. Compression of individual sequences via variable-rate coding. IEEE Trans. Inf. Theory 1978, 24, 530-536.
9. Gopalratnam, K.; Cook, D.J. Online sequential prediction via incremental parsing: The active LeZi algorithm. IEEE Intell. Syst. 2007, 22, 52-58.
10. Song, L.; Kotz, D.; Jain, R.; He, X. Evaluating next-cell predictors with extensive Wi-Fi mobility data. IEEE Trans. Mobile Comput. 2006, 5, 1633-1649.
11. Rodriguez-Carrion, A.; Garcia-Rubio, C.; Campo, C. Performance evaluation of LZ-based location prediction algorithms in cellular networks. IEEE Commun. Lett. 2010, 14, 707-709.
12. Chen, L.; Lv, M.; Chen, G. A system for destination and future route prediction based on trajectory mining. Pervasive Mobile Comput. 2010, 6, 657-676.
13. Nicholson, A.J.; Noble, B.D. BreadCrumbs: Forecasting mobile connectivity. In Proceedings of the 14th ACM international Conference on Mobile Computing and Networking, San Francisco, CA, USA, 14-19 September 2008; ACM: New York, NY, USA, 2008; pp. 46-57.
14. Ashbrook, D.; Starner, T. Using GPS to learn significant locations and predict movement across multiple users. Pers. Ubiquitous Comput. 2003, 7, 275-286.
15. Roy, A.; Das, S.K.; Basu, K. A predictive framework for location-aware resource management in smart homes. IEEE Trans. Mobile Comput. 2007, 6, 1270-1283.
16. Kim, J.; Helmy, A. Poster abstract: The challenges of accurate mobility prediction for ultra mobile users. ACM SIGMOBILE Mobile Comput. Commun. Rev. 2010, 13, 58-61.
17. Bayir, M.A.; Demirbas, M.; Eagle, N. Mobility profiler: A framework for discovering mobility profiles of cell phone users. Pervasive Mobile Comput. 2010, 6, 435-454.
18. Djuknic, G.; Richton, R. Geolocation and assisted GPS. Computer 2001, 34, 123-125.
19. Hightower, J.; Borriello, G. Location systems for ubiquitous computing. Computer 2001, 34, 57-66.
20. Zhao, Y. Standardization of mobile phone positioning for 3G systems. IEEE Commun. Mag. 2002, 40, 108-116.
21. Laasonen, K. Route prediction from cellular data. InWorkshop on Context-Awareness for Proactive Systems (CAPS), Helsinki, Finland, 16-17 June 2005.
22. Liu, T.; Bahl, P.; Chlamtac, I. Mobility modeling, location tracking, and trajectory prediction in wireless ATM networks. IEEE J. Sel. Areas Commun. 1998, 16, 922-936.
23. Petzold, J.; Bagci, F.; Trumler, W.; Ungerer, T. Comparison of different methods for next location prediction. In Processing of Euro-Par 2006 Parallel, Dresden, Germany, 28 August-1 September 2006; Nagel, W., Walter, W., Lehner, W., Eds.; Springer: Berlin, Germany, 2006; Volume 4128, pp. 909-918.
24. Sigg, S.; Haseloff, S.; David, K. An alignment approach for context prediction tasks in UbiComp environments. IEEE Pervasive Comput. 2010, 9, 90-97.
25. Petzold, J.; Bagci, F.; Trumler, W.; Ungerer, T. Next location prediction within a smart office building. In Proceedings of 1st International Workshop on Exploiting Context Histories in Smart Environments (ECHISE'05) at the 3rd International Conference on Pervasive Computing, Munich, Germany, 11 May 2005.
26. Ma, Y.; Hankins, R.; Racz, D. iLoc: A framework for incremental location-state acquisition and prediction based on mobile sensors. In Proceedings of the 18th ACM Conference on Information and Knowledge Management, Hong Kong, 2-6 November 2009; ACM: New York, NY, USA, 2009; pp. 1367-1376.
27. Katsaros, D.; Nanopoulos, A.; Karakaya, M.; Yavas, G.; Ulusoy, Ö.; Manolopoulos, Y. Clustering Mobile Trajectories for Resource Allocation in Mobile Environments; IDA: Singapore, 2003; pp. 319-329.
28. Anagnostopoulos, T.; Anagnostopoulos, C.; Hadjiefthymiades, S. An Online Adaptive Model for Location Prediction; In Third International ICST Conference on Autonomic Computing and Communication Systems, Limassol, Cyprus, 9-11 September 2009; pp. 64-78.
29. Katsaros, D.; Manolopoulos, Y. Prediction in wireless networks by markov chains. IEEE Wirel. Commun. 2009, 16, 56-63.
30. Vitter, J.S.; Krishnan, P. Optimal prefetching via data compression. J. ACM 1996, 43, 771-793.
31. Cleary, J.G.; Teahan, W.J. Unbounded length contexts for PPM. Comput. J. 1997, 40, 67-75.
32. Eagle, N.; Pentland, A.; Lazer, D. Inferring social network structure using mobile phone data. Proc. Natl. Acad Sci. (PNAS) 2009, 106, 15274-15278.