Personalising Map Feature Content for Mobile Map Users

  • Joe Weakliam
  • David Wilson
  • Michela Bertolotto
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)


Several challenges arise when displaying maps on mobile devices. Users encounter problems dealing with information overload and mapping interface interaction while on the move – issues of human-computer interaction. In addition, to effectively display maps on mobile devices, developers must address restrictions related to screen size and limited bandwidth – issues of computational efficiency. We have developed MAPPER, a novel approach for delivering personalised maps to mobile devices, which addresses mobile mapping issues from both perspectives. MAPPER generates maps containing specific spatial feature content that is tailored to the explicit preferences of users with contrasting requirements by monitoring the interactions of individuals when browsing maps. All interactions between users and maps are captured implicitly and are used to infer individual and group preferences related to specific map feature content. MAPPER provides an effective and efficient means of delivering and representing maps on mobile devices, which addresses information overload by providing exactly the map information necessary to suit user interaction preferences. In turn, tailoring map content to user preferences considerably reduces the size of vector datasets necessary to transmit and render maps. This chapter describes the map personalisation approach in MAPPER and presents a user study showing the benefits of providing a diverse set of individuals with personalised map feature content when engaged in mobile mapping tasks.


Mobile Device Feature Level User Preference User Profile User Interest 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Agrawal, R., Imielinski, T., and Swami, A.N. (1993): Mining association rules between sets of items in large databases. Proceedings of the ACM SIGMOD International Conference on Management of Data, Washington, D.C, pp. 207-216.Google Scholar
  2. Fink, J. and Kobsa, A. (2002): User modelling in personalised city tours. Intelligence Review 18(1), pp. 33-74.CrossRefGoogle Scholar
  3. Fischer, G. (2001): User modeling in human-computer interaction. User Modeling and User-Adapted Interaction 11(1-2), pp. 65-86.CrossRefGoogle Scholar
  4. Hinze, A. and Voisard A. (2003): Locations- and time-based information delivery in tourism. Proceedings of the 8 th International Symposium on Advances in Spatial and Temporal Databases, Santorini Island, Greece, pp. 489-507.Google Scholar
  5. Horvitz, E., Breese, J., Heckerman, D., Hovel, D., and Rommelse, K. (1998): The Lumiere Project: Bayesian user modelling for inferring the goals and needs of software users. Proceedings of the 14 th Conference on Uncertainty in Artificial Intelligence, Madison, Wisconsin, pp. 256-265.Google Scholar
  6. Kelly, D. and Belkin, N. (2001): Reading time, scrolling and interaction: Exploring implicit sources of user preferences for relevance feedback during interactive information retrieval. Proceedings of the 24th Annual International Conference on Research and Development in Information Retrieval (SIGIR ’01), New Orelans, LA, pp. 408-409.Google Scholar
  7. Kelly, D. and Teevan, J. (2003): Implicit feedback for inferring user preference: A bibliography. SIGIR Forum 37(2), pp. 18-28.CrossRefGoogle Scholar
  8. Kim, J., Oard, D.W., and Romanik, K. (2001): User modelling for information access based on implicit feedback. Proceedings of the ISKO France Workshop on Information Filtering, Paris, France.Google Scholar
  9. Linton, F., Joy, D., and Schaefer, H.P. (1999): Building user and expert models by long-term observation of application usage. Proceedings of the International Conference on User Modelling(UM99), Banff, Canada, pp. 129-138.Google Scholar
  10. MapQuest (2006): Scholar
  11. OpenMap (2006): Scholar
  12. Oppermann, R. and Specht, M. (2000): A context-sensitive nomadic information system as an exhibition guide. Proceedings of the Second International Symposium on Handheld and Ubiquitous Computing (HUC 2000), Bristol, UK, pp. 127-142.Google Scholar
  13. Oracle Spatial: Scholar
  14. Reichenbacher, T. (2001a): The world in your pocket – towards a mobile cartography. Proceedings of the 20 th International Cartographic Conference (ICC 2001), Beijing, China, pp. 2514-2521.Google Scholar
  15. Reichenbacher, T. (2001b): Adaptive concepts for a mobile cartography. Supplement Journal of Geographical Sciences 11, pp. 43-53.Google Scholar
  16. Schmidt-Belz, B., Nick, A., Poslad, S., and Zipf, A. (2002): Personalised and location-based mobile tourism services. Proceedings of Mobile HCI‘02 with the Workshop on “Mobile Tourism Support Systems”, Pisa, Italy.Google Scholar
  17. Tiger/Line files (2006): Scholar
  18. Weakliam, J., Wilson, D., and Bertolotto, M. (2005a): Implicit interaction profiling for recommending spatial content. Proceedings of the 14 th International Symposium on Advances in Geographic Information Systems (ACMGIS’05), Bremen, Germany, pp. 285-294.Google Scholar
  19. Weakliam, J., Lynch, D.B., Doyle, J., Bertolotto, M., and Wilson, D. (2005b): Delivering personalized context-aware spatial information to mobile devices. Proceedings of the 5 th International Workshop on Web and Wireless Geographic Information Systems (W2GIS’05), Lausanne, Switzerland, pp. 194-205.Google Scholar
  20. Weisenberg, N., Voisard, A., and Gartmann, R. (2004): Using ontologies in personalised mobile applications. Proceedings of the 12 th annual ACM international workshop on Geographic Information Systems (ACMGIS’04), Washington DC, pp. 2-11.Google Scholar
  21. Yahoo! Maps (2006): Scholar
  22. Zipf, A. (2002): User-adaptive maps for location-based services (LBS) for tourism. Proceedings of the 9th International Conference for Information and Communication Technologies in Tourism (ENTER 2002), Innsbruck, Austria, pp.329-338.Google Scholar
  23. Zipf, A. and Richter, K.F. (2002): Using focus maps to ease map reading. Developing smart applications for mobile devices. Künstliche Intelligenz (KI). Special issue: Spatial Cognition (4), pp. 35-37.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Joe Weakliam
    • 1
  • David Wilson
    • 2
  • Michela Bertolotto
    • 1
  1. 1.School of Computer Science and InformaticsUniversity College DublinBelfieldIreland
  2. 2.Department of Software and Information SystemsUniversity of North Carolina at CharlotteUSA

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