Enhancing Traveler Context through Transferable Activity Patterns

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Mobile Computing, Applications, and Services (MobiCASE 2012)

Abstract

Develo** a model of the needs of a mobile traveler is critical to good personalization. Transportation planners have been modeling these needs for years, but these models have not been used to date due to two outstanding questions: 1) are they applicable to individual travelers 2) are they useful beyond the studied region. This study demonstrates these studies can directly enhance the model of mobile users, and be done in a practical way through the transference of activity patterns across cities. This work then demonstrates how these studies can be combined with patterns of an individual mobile user successfully.

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References

  1. Krumm, J., Horvitz, E.: Predestination: Inferring Destinations from Partial Trajectories. In: Dourish, P., Friday, A. (eds.) UbiComp 2006. LNCS, vol. 4206, pp. 243–260. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  2. Liao, L., Fox, D., Kautz, H.: Location-based activity recognition using relational Markov networks. In: Proceedings of the International Joint Conference on Artificial Intelligence, IJCAI (2005)

    Google Scholar 

  3. Zheng, V.W., Zheng, Y., **e, X., Yang, Q.: Collaborative location and activity recommendations with GPS history data. In: Proceedings of the 19th International Conference on World Wide Web (WWW 2010), pp. 1029–1038. ACM (2010)

    Google Scholar 

  4. Williams, C.A., Mohammadian, A., Nelson, P.C., Doherty, S.T.: Mining Sequential Association Rules for Traveler Context Prediction. In: Proceedings of the First International Workshop on Computational Transportation Science held at The International Conference on Mobile and Ubiquitous Systems: Networks and Services, MOBIQUITOUS 2008 (2008)

    Google Scholar 

  5. Williams, C.A., Nelson, P.C., Mohammadian, A(K.): Attribute Constrained Rules for Partially Labeled Sequence Completion. In: Perner, P. (ed.) ICDM 2009. LNCS, vol. 5633, pp. 338–352. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  6. Timmermans, H.: Progress in Activity-Based Analysis. Elsevier (2005)

    Google Scholar 

  7. Doherty, S.T., Mohammadian, A.: The Validity of Using Activity Type to Structure Tour-based Scheduling Models. In: Proc. of 86th Annual Meeting of the Transportation Research Board, Washington D.C. (January 2007)

    Google Scholar 

  8. Agrawal, R., Srikant, R.: Mining sequential patterns. In: Yu, P.S., Chen, A.S.P. (eds.) Eleventh International Conference on Data Engineering, Taipei, Taiwan, pp. 3–14. IEEE Computer Society Press (1995)

    Google Scholar 

  9. Doherty, S., Nemeth, E., Roorda, M., Miller, E.: Design and Assessment of the Toronto Area Computerized Household Activity Scheduling Survey. Journal of the Transportation Research Board 1894, 140–149 (2004)

    Article  Google Scholar 

  10. NuStats: 2001 Atlanta Household Travel Survey: Final Report. Technical report, Atlanta Regional Commision (April 2003)

    Google Scholar 

  11. NuStats: 2002 Anchorage Household Travel Survey Technical Report. Technical report, Municipality of Anchorage (September 2002)

    Google Scholar 

  12. Frignani, M.Z., Auld, J., Mohammadian, A., Williams, C., Nelson, P.: Urban Travel Route and Activity Choice Survey (UTRACS): An internet-based prompted recall activity travel survey using GPS data. In: Proceedings of 89th Annual Meeting of the Transportation Research Board, Washington D.C. (January 2010)

    Google Scholar 

  13. Arentze, T., Hofman, F., van Mourik, H., Timmermans, H.: Spatial Transferability of the Albatross Model System: Empirical Evidence from Two Case Studies. Transportation Research Record: Journal of the Transportation Research Board 1805, 1–7 (2002)

    Article  Google Scholar 

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© 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering

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Williams, C.A., Mohammadian, A., Auld, J., Doherty, S.T. (2013). Enhancing Traveler Context through Transferable Activity Patterns. In: Uhler, D., Mehta, K., Wong, J.L. (eds) Mobile Computing, Applications, and Services. MobiCASE 2012. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 110. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36632-1_26

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  • DOI: https://doi.org/10.1007/978-3-642-36632-1_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36631-4

  • Online ISBN: 978-3-642-36632-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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