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Design and Implementation of a Framework for Context-Aware Preference Queries

  • Received : 2012.10.12
  • Accepted : 2012.10.24
  • Published : 2012.12.30

Abstract

In this paper we present a framework for a novel kind of context-aware preference query composition whereby queries for the Preference SQL system are created. We choose a commercial e-business platform for outdoor activities as a use case and develop a context model for this domain within our framework. The suggested model considers explicit user input, domain-specific knowledge, contextual knowledge and location-based sensor data in a comprehensive approach. Aside from the theoretical background of preferences, the optimization of preference queries and our novel generator based model we give special attention to the aspects of the implementation and the practical experiences. We provide a sketch of the implementation and summarize our user studies which have been done in a joint project with an industrial partner.

Keywords

References

  1. W. Kiebling, "Preference queries with SV-semantics," Proceedings of the 11th International Conference on Management of Data, Goa, India, 2005, pp. 15-26.
  2. K. Stefanidis, G. Koutrika, and E. Pitoura, "A survey on representation, composition and application of preferences in database systems," ACM Transactions on Database Systems, vol. 36, no. 3, article no. 19, 2011.
  3. W. Kiebling, "Foundations of preferences in database systems," Proceedings of the 28th International Conference on Very Large Data Bases, Hong Kong, China, 2002, pp. 311-322.
  4. J. Chomicki, "Database querying under changing preferences," Annals of Mathematics and Artificial Intelligence, vol. 50, no. 1-2, pp. 79-109, 2007. https://doi.org/10.1007/s10472-007-9072-3
  5. W. Kiebling, M. Soutschek, A. Huhn, P. Roocks, M. Endres, S. Mandl, F. Wenzel, and A. Zelend, "Context-aware preference search for outdoor activity platforms," University of Augsburg, Augsburg, Germany, Technical Report 2011-15, 2011.
  6. J. J. Levandoski, M. E. Khalefa, and M. F. Mokbel, "An overview of the CareDB context and preference-aware database system," IEEE Data Engineering Bulletin, vol. 34, no. 2, pp. 41-46, 2011.
  7. E. Pitoura, K. Stefanidis, P. Vassilidis, "Contextual Database Preferences," IEEE Data Engineering Bulletin, vol. 34, no. 2, pp. 20-27, 2011.
  8. A. H. van Bunningen, L. Feng, and P. M. G. Apers, "A context- aware preference model for database querying in an ambient intelligent environment," Proceedings of the 17th International Conference on Database and Expert Systems Applications, Krakow, Poland, 2006, pp. 33-43.
  9. K. Stefanidis, E. Pitoura, and P. Vassiliadis, "Adding context to preferences," Proceedings of the IEEE 23rd International Conference on Data Engineering, Istanbul, Turkey, 2007, pp. 846-855.
  10. J. Chomicki, "Preference formulas in relational queries," ACM Transactions on Database Systems, vol. 28, no. 4, pp. 427-466, 2003. https://doi.org/10.1145/958942.958946
  11. W. Kiebling, M. Endres, and F. Wenzel, "The preference SQL System: an overview," IEEE Database Engineering Bulletin, vol. 34, no. 2, pp. 11-18, 2011.
  12. F. Wenzel, M. Endres, S. Mandl, and W. Kiebling, "Complex preference queries supporting spatial applications for user groups," Proceedings of the VLDB Endowment, vol. 5, no. 12, pp. 1946-1949, 2012.
  13. L. Barkhuus and A. Dey, "Is context-aware computing taking control away from the user? Three levels of interactivity examined," Proceedings of the 5th International Conference on Ubiquitous Computing, 2003, Seattle, WA, pp. 150-156.
  14. H. Gibson and A. Yiannakis, "Tourist roles: needs and the lifecourse," Annals of Tourism Research, vol. 29, no. 2, pp. 358-383, 2002. https://doi.org/10.1016/S0160-7383(01)00037-8
  15. D. Mindolin and J. Chomicki, "Discovering relative importance of skyline attributes," Proceedings of the VLDB Endowment, vol. 2, no. 1, pp. 610-621, 2009.
  16. Preference SQL, http://www.preferencesql.com.
  17. W. Kiebling and G. Kostler, "Preference SQL: design, implementation, experiences," Proceedings of the 28th International Conference on Very Large Data Bases, Hong Kong, China, 2002, pp. 990-1001.
  18. A. Arvanitis and G. Koutrika, "Towards preference-aware relational databases," Proceedings of the IEEE 28th International Conference on Data Engineering, Washington, DC, 2002, pp. 426-437.
  19. B. Hafenrichter and W. Kießling, "Optimization of relational preference queries," Proceedings of the 16th Australasian Database Conference, Darlinghurst, Australia, 2005, pp. 175-184.
  20. M. Endres and W. Kießling, "Semi-skyline optimization of constrained skyline queries," Proceedings of the 22nd Australasian Database Conference, Perth, Australia, 2011.
  21. T. Preisinger and W. Kießling, "The hexagon algorithm for Pareto preference queries," Proceedings of the 3rd Multidisciplinary Workshop on Advances in Preference Handling, Vienna, Austria, 2007.
  22. P. Godfrey, R. Shipley, and J. Gryz, "Maximal vector computation in large data sets," Proceedings of the 31st International Conference on Very Large Data Bases, Trondheim, Norway, 2005, pp. 229-240.
  23. B. Moller and P. Roocks, "An algebra of layered complex preferences," Relational and Algebraic Methods in Computer Science, Lecture Notes in Computer Science vol. 7560, W. Kahl and T. G. Griffin, editors, Heidelberg: Springer Berlin, pp 294-309, 2012.