Advertisement

Advanced Recommendation Models for Mobile Tourist Information

  • Annika Hinze
  • Saijai Junmanee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4275)

Abstract

Personalized recommendations in a mobile tourist information system suffer from a number of limitations. Most pronounced is the amount of initial user information needed to build a user model. In this paper, we adopt and extend the basic concepts of recommendation paradigms by exploiting a user’s personal information (e.g., preferences, travel histories) to replace the missing information. The designed algorithms are embedded as recommendation services in our TIP prototype. We report on the results of our analysis regarding effectiveness and performance of the recommendation algorithms. We show how a number of limiting factors were successfully eliminated by our new recommender strategies.

Keywords

Recommender System Collaborative Filter Similar User Recommendation Algorithm Travel History 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Amendola, I., Cena, F., Console, L., Crevola, A., Gena, C., Goy, A., Modeo, S., Perrero, M., Torre, I., Toso, A.: UbiquiTO: A multi-device adaptive guide. In: Mobile HCI: Mobile Human-Computer Interaction, Glasgow, UK (September 2004)Google Scholar
  2. 2.
    Burke, R.: Knowledge-based and collaborative-filtering recommender systems. In: Proceedings of the Workshop on AI and Electronic Commerce. AAAI 1999, Orlando, Florida (1999)Google Scholar
  3. 3.
    Burke, R., Hammond, K., Yong, B.: The findme approach to assisted browsing. IEEE Expert: Intelligent Systems and Their Applications 12(4), 32–40 (1997)Google Scholar
  4. 4.
    Chen, H., Chen, A.: A music recommendation system based on music data grouping and user interest. In: Proceedings of the tenth international conference on Information and knowledge management, Atlanta, Georgia, USA (October 2001)Google Scholar
  5. 5.
    Cheverst, K., Mitchell, K., Davies, N.: The role of adaptive hypermedia in a context-aware tourist guide. Communication of the ACM 45(5), 47–51 (1997)Google Scholar
  6. 6.
    Hayes, C., Massa, P., Avesani, P., Cunningham, P.: An on-line evaluation framework for recommender systems. In: Workshop on Personalization and Recommendation in E-Commerce, Malaga, Spain (May 2002)Google Scholar
  7. 7.
    Herlocker, J., Konstan, J., Borchers, A., Riedl, J.: An algorithmic framework for performing collaborative filtering. In: Proceedings of the SIGIR 1999, Berkley, California, USA. (August 1999)Google Scholar
  8. 8.
    Herlocker, J., Konstan, J., Terveen, L., Riedl, J.: Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems 22(1), 5–53 (2004)CrossRefGoogle Scholar
  9. 9.
    Hinze, A., Junmanee, S.: Travel recommendations in a mobile tourist information system. In: Proceedings of Information Systems and its Application ISTA 2005, Palmerston North, New Zealand (May 2005)Google Scholar
  10. 10.
    Hinze, A., Voisard, A.: Location and time-based information delivery in tourism. In: Proceedings of Advances in Spatial and Temporal Databases, 8th International Symposium, Santorini Island, Greece (July 2003)Google Scholar
  11. 11.
    Junmanee, S., Hinze, A.: Design and implementation of an advanced recommendation component in the tourist information system tip. Technical Report X/2006, University of Waikato, Computer Science Department, Hamilton, New Zealand, (June 2006), based on Master’s Thesis Google Scholar
  12. 12.
    Klante, P., Krösche, J., Boll, S.: AccesSights – A multimodal location-aware mobile tourist information system. In: Miesenberger, K., Klaus, J., Zagler, W.L., Burger, D. (eds.) ICCHP 2004. LNCS, vol. 3118, pp. 287–294. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  13. 13.
    Melvile, P., Mooney, R., Nagarajan, R.: Content-boosted filtering for improved recommendations. In: Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI 2002), Edmonton, Canada (July 2002)Google Scholar
  14. 14.
    Middleton, S.E., Shadbolt, N., Roure, D.D.: Ontological user profiling in recommender systems. ACM Transactions on Information Systems 22(1), 54–88 (2004)CrossRefGoogle Scholar
  15. 15.
    Mooney, R., Roy, L.: Content-based book recommending using learning for text categorization. In: Proceedings of the fifth ACM conference on Digital libraries, San Antonio, Texas, USA (June 2000)Google Scholar
  16. 16.
    Papagelis, M., Plexousakis, D.: Qualitative analysis of user-based and item-based prediction algorithms for recommendation agents. In: Proc. of the Workshop for Cooperative Information Agents VIII, Erfurt, Germany (September 2004)Google Scholar
  17. 17.
    Paris, C.: Information delivery for tourism. IEEE Intelligent System 17(6), 61–63 (2002)Google Scholar
  18. 18.
    Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: Proceedings of 10th International World Wide Web Conference, WWW10, Hong Kong (May 2001)Google Scholar
  19. 19.
    Scottish citylink online bus ticket booking, Available at: http://www.citylink.co.uk/howtobuy.htm (accessed on 19/4/2005)
  20. 20.
    Simcock, T., Hillenbrand, S., Thomas, B.: Developing a location based tourist guide application. In: Proceedings of the Australasian information security workshop conference CRPTIS 21, ACSW frontiers, Australia (2003)Google Scholar
  21. 21.
    Sinha, R., Swearingen, K.: The role of transparency in recommender systems. In: Proceedings of Conference on Human Factors in Computing Systems, London, UK, April 2002, pp. 830–831 Google Scholar
  22. 22.
    Vozalis, E., Margaritis, K.: Analysis of recommender system’s algorithm. In: Sixth Hellenic-European Conference on Computer Mathematics and its Applications(HERCMA), Athens, Greece (September 2003)Google Scholar
  23. 23.
    Zipf, A.: Adaptive context-aware mobility support for tourists. IEEE Intelligent System 17(6), 57–59 (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Annika Hinze
    • 1
  • Saijai Junmanee
    • 1
  1. 1.University of WaikatoNew Zealand

Personalised recommendations