A Mobile Location-Aware Recommendation System

Semih Utku, Canan Eren Atay


Improvements in mobile technology provide greater personal information accessibility, data incorporation, and public resources accessibility, “anytime, anywhere”. Smartphones are not only devices that make phone calls, but have also become a gateway to the Internet. Mobile devices offer the capabilities of usage flexibility, mobility, fast wireless communication, and location-awareness. Location is determined by GPS satellite tracking, position relative to GSM base stations, and the device's media access control. Similarly, usage of social networks is increasing steadily. Widespread usage of social networks introduces new requirements of Internet application. Users of such networks share their ideas and interests, as well as the activities they plan to attend. In addition, they follow other users’ information and shape their planned activities accordingly. In this study, an intelligent context-aware system is described. In this field, context-awareness is a mobile paradigm in which applications can discover and take advantage of contextual information, such as user location, nearby people and devices, and user activity. This system provides an activity list that users plan to attend. Our recommender system creates results based on data mining techniques, by using personal identification data and user activities. The recommender system brings novel methodology to the activity-decision process by utilizing the right location and real-time information.


  1. Rao, B., Minakakis, L. 2003. Evolution of mobile location-based services, Communications of the ACM., 46(12), pp.61-65.
  2. Fahy, P., Clarke, S., 2004. CASS a middleware for mobile context-aware applications. In Workshop on Context Awareness, MobiSys.
  3. Dieberger A., 2003. Social connotations of space in the design for virtual communities and social navigation. Computer Supported Cooperative Work, Springer London, pp. 293-313.
  4. Dourish, P., Chalmers, M., 1994. Running Out of Space : Models of Information Navigation. HCI'94, Glasgow, UK, pp.2-3.
  5. Hook, K., Benyon, D., Munro, A., 2003. Designing Information Spaces: The Social Navigation Approach. Berlin: Springer-Verlag.
  6. Gay, G., 2009. Context-Aware Mobile Computing: Affordances of Space, Social Awareness, and Social Influence. Synthesis Lectures on Human-Centered Informatics, pp. 1-62.
  7. Yavas, G. et al., 2005. A data mining approach for location prediction in mobile environments. Data & Knowledge Engineering, 54(2), pp.121-146.
  8. Baldauf, M., Dustdar, S., Rosenberg, F., 2007. A Survey on Context Aware Systems. Int. J. Ad Hoc Ubiquitous Comput., 2(4), pp.263-277.
  9. Lee, J. et al., 2006. Location-Aware Agent Using Data Mining for the Distributed Location-Based Services. Computational Science and Its Applications - ICCSA., Springer Berlin Heidelberg, pp. 867-876.
  10. Hightower, J., Borriello, G., 2001. A Survey and Taxonomy of Location Systems for Ubiquitous Computing. University of Washington, Seattle, WA.
  11. Fischmeister, S., 2003. Mobile Software Agents for Location-based Systems. In Proceedings of the NODe Agent-related Conference on Agent Technologies, Infrastructures, Tools, and Applications for Eservices. NODe'02. Berlin, Heidelberg: SpringerVerlag, pp. 226-239.
  12. Ricci, F., et al., 2011. Recommender Systems Handbook. Springer.
  13. Burke, R., 2007. The Adaptive Web - Hybrid Web Recommender Systems. Springer-Verlag, pp. 377- 408.
  14. Bellavista, P., et al., 2012. A Survey of Context Data Distribution for Mobile Ubiquitous Systems. ACM Computing Surveys., 44( 4):24.
  15. Costa, P., et al., 2004. Towards a service platform for mobile context-aware applications. ICUW, pp. 48-61.
  16. Chen, G., Kotz, D., 2002. Solar: An open platform for context-aware mobile applications. In Proceedings of the First International Conference on Pervasive Computing, pp. 41- 47.
  17. Church K., et al., 2008. A Large Scale Study of European Mobile Search Behaviour. MobileHCI'08, Amsterdam, the Netherlands, pp.13-22.
  18. Yi, J., Maghoul F., Pedersen, J., 2008. Deciphering Mobile Search Patterns: A Study of Yahoo! Mobile Search Queries. International World Wide Web Conference Committee (IW3C2), Beijing, China, pp.257-266.
  19. Amin A., et al., 2006. Fancy a Drink in Canary Wharf?: A User Study on Location-Based Mobile Search. Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction, pp 736- 749.
  20. Sinnott, R.W., 1984. Virtues of the Haversine. Sky and Telescope, 68(2), p.159.

Paper Citation

in Harvard Style

Utku S. and Eren Atay C. (2014). A Mobile Location-Aware Recommendation System . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014) ISBN 978-989-758-048-2, pages 176-183. DOI: 10.5220/0005053001760183

in Bibtex Style

author={Semih Utku and Canan Eren Atay},
title={A Mobile Location-Aware Recommendation System},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)},

in EndNote Style

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)
TI - A Mobile Location-Aware Recommendation System
SN - 978-989-758-048-2
AU - Utku S.
AU - Eren Atay C.
PY - 2014
SP - 176
EP - 183
DO - 10.5220/0005053001760183