Mining User Movement Behavior Patterns in a Mobile Service Environment

IEEE Transactions on Systems, Man, and Cybernetics Part A: Systems and Humans

Volumn 42, Issue 1, 2012, Pages 87-101

  Chen, Tzung Shi ^a   Chou, Yen Ssu ^b   Chen, Tzung Cheng ^c  

^a NATIONAL UNIVERSITY OF TAINAN   (Taiwan)

^b NATIONAL TSING HUA UNIVERSITY   (Taiwan)

^c CHANG JUNG CHRISTIAN UNIVERSITY   (Taiwan)

Author keywords

Data mining; mobile access patterns; mobile services; mobility prediction; spatio temporal mining

Indexed keywords

BEHAVIORAL RESEARCH; GRAPH ALGORITHMS; JOINING; LOCATION BASED SERVICES; PATTERN MATCHING;

BI-PARTITE GRAPH MATCHING; EXPERIMENTAL EVALUATION; GRAPH-MATCHING ALGORITHMS; MOBILE ACCESS PATTERNS; MOBILE SERVICE; MOBILITY PREDICTIONS; PREDICTION MECHANISMS; SPATIO-TEMPORAL MININGS;

DATA MINING;

EID: 84655163887     PISSN: 10834427     EISSN: 15582426     Source Type: Journal    
DOI: 10.1109/TSMCA.2011.2159583     Document Type: Article

References (27)

1. R. Agrawal and R. Srikant, “Fast algorithms for mining association rules in large databases,” in Proc. 20th Int. Conf. Very Large Databases, 1994, pp. 487–499.
2. U. Bellur and R. Kulkarni, “Improved matchmaking algorithm for semantic web services based on bipartite graph matching,” in Proc. IEEE ICWS, Salt Lake City, UT, Jul. 2007, pp. 86–93.
3. N. Bicocchi, M. Baumgarten, N. Brgulja, R. Kusber, M. Mamei, M. Mulvenna, and F. Zambonelli, “Self-organized data ecologies for pervasive situation-aware services: The knowledge networks approach,” IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol. 40, no. 4, pp. 789–802, Jul. 2010.
4. Y. C. Chang, L. D. Bergman, V. Castelli, C. -S. Li, M. -L. Lo, and J. R. Smith, “The onion technique: Indexing for linear optimization queries,” in Proc. Int. Conf. ACM SIGMOD, Dallas, TX, May 2000, pp. 391–402.
5. S. Chaudhuri, L. Gravano, and A. Marian, “Optimizing top-k selection queries over multimedia repositories,” IEEE Trans. Knowl. Data Eng., vol. 16, no. 8, pp. 992–1009, Aug. 2004.
6. H. Cheng, X. Yan, and J. Han, “IncSpan: Incremental mining of sequential patterns in a large database,” in Proc. 10th ACM SIGKDD Int. Conf. Knowl. Discovery Data Mining, Seattle, WA, Aug. 2004, pp. 527–532.
7. M. Fayyazi, D. Kaeli, and W. Meleis, “Parallel maximum weight bipartite matching algorithms for scheduling in input-queued switches,” in Proc. 18th IPDPS, Santa Fe, NM, Apr. 2004, pp. 4–11.
8. J. L. Huang, M. S. Chen, and W. C. Peng, “Exploring group mobility for replica data allocation in a mobile environment,” in Proc. ACM Int. Conf. Inf. Knowl. Manage., New Orleans, LA, Nov. 2003, pp. 161–168.
9. Y. F. Huang and J. M. Hsu, “Mining web logs to improve hit ratios of prefetching and caching,” Knowl. -Based Syst., vol. 21, no. 1, pp. 62–69, Feb. 2008.
10. Y. F. Huang and K. H. Lin, “Global data allocation based on user behaviors in mobile computing environments,” Comput. Commun., vol. 31, no. 10, pp. 2420–2427, Jun. 2008.
11. I. F. Ilyas, W. G. Aref, and A. K. Elmagarmid, “Supporting top-k join queries in relational databases,” J. Very Large Databases, vol. 13, no. 3, pp. 207–221, Sep. 2004.
12. L. Lancieri and N. Durand, “Internet user behavior: Compared study of the access traces and application to the discovery of communities,” IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol. 36, no. 1, pp. 208–219, Jan. 2006.
13. S. C. Lee, J. Paik, J. Ok, I. Song, and U. M. Kim, “Efficient mining of user behaviors by temporal mobile access patterns,” Int. J. Comput. Sci. Security, vol. 7, no. 2, pp. 285–291, Feb. 2007.
14. W. P. Lee, “Deploying personalized mobile services in an agent-based environment,” Expert Syst. Appl., vol. 32, no. 4, pp. 1194–1207, May 2007.
15. T. Li, W. Peng, C. Perng, S. Ma, and H. Wang, “An integrated data-driven framework for computing system management,” IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol. 40, no. 1, pp. 90–99, Jan. 2010.
16. H. Liu and V. Keselj, “Combined mining of web server logs and web contents for classifying user navigation patterns and predicting usersʼn future requests,” Data Knowl. Eng., vol. 61, no. 2, pp. 304–330, May 2007.
17. J. Monnot and S. Toulouse, “The path partition problem and related problems in bipartite graphs,” Oper. Res. Lett., vol. 35, no. 5, pp. 677–684, Sep. 2007.
18. Z. Pabarskaite and A. Raudys, “A process of knowledge discovery from web log data: Systematization and critical review,” J. Intell. Inf. Syst., vol. 28, no. 1, pp. 79–104, Feb. 2007.
19. A. Pashtan, A. Heusser, and P. Scheuermann, “Personal service areas for mobile web applications,” IEEE Internet Comput., vol. 8, no. 6, pp. 34–39, Nov./Dec. 2004.
20. W. C. Peng and M. S. Chen, “Developing data allocation schemes by incremental mining of user moving patterns in a mobile computing system,” IEEE Trans. Knowl. Data Eng., vol. 15, no. 1, pp. 70–85, Jan./Feb. 2003.
21. W. C. Peng and M. S. Chen, “Shared data allocation in a mobile computing system: Exploring local and global optimization,” IEEE Trans. Parallel Distrib. Syst., vol. 16, no. 4, pp. 374–384, Apr. 2005.
22. I. J. Perez, F. J. Cabrerizo, and E. Herrera-Viedma, “A mobile decision support system for dynamic group decision-making problems,” IEEE Trans. Syst., Man, Cybern. A, Syst., Humans, vol. 40, no. 6, pp. 1244–1256, Nov. 2010.
23. V. Terziyan and O. Vitko, “Bayesian metanetworks for modelling user preferences in mobile environment,” in KI 2003: Advances in Artificial Intelligence. Berlin, Germany: Springer-Verlag, 2003, pp. 370–384.
24. H. -W. Tsai, C. -P. Chu, and T. -S. Chen, “Mobile object tracking in wireless sensor networks,” Comput. Commun., vol. 30, no. 8, pp. 1811–1825, Jun. 2007.
25. V. S. Tseng and E. H. -C. Lu, “Energy-efficient real-time object tracking in multi-level sensor networks by mining and predicting movement patterns,” J. Syst. Softw., vol. 82, no. 4, pp. 697–706, Apr. 2009.
26. V. S. Tseng, R. H. -C. Lu, and C. -H. Huang, “Mining temporal mobile sequential patterns in location-based service environments,” in Proc. 13th ICPADS, Hsinchu, Taiwan, Dec. 2007, vol. 1, pp. 1–8.
27. G. Yavas, D. Katsaros, Ö. Ulusoy, and Y. Manolopoulos, “A data mining approach for location prediction in mobile environments,” Data Knowl. Eng., vol. 54, no. 2, pp. 121–146, Aug. 2005.