Using Rules to Develop a Personalized and Social Location Information System for the Semantic Web

  • Iosif Viktoratos
  • Athanasios K. Tsadiras
  • Nick Bassiliades
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8620)


In this work, the design and implementation of an innovative context-aware location based social networking service is presented. The proposed system, called “Geosocial SPLIS”, utilizes Semantic Web technologies to deliver personalized information to the end user. It addresses some drawbacks of knowledge-based personalization systems and aims to provide a collaborative knowledge creation platform for other systems. To achieve this, it a) collects data from external sources such as Google Places API and Google+ b) adopts the ontology to represent people and places profiles, c) provides a web editor for adding rules (modeling user preferences and group-targeted place offers) at run time, d) uses RuleML and Jess rules to represent these rules, e) combines at run-time the above to match user context with up to date information, presented on Google Maps and f) matches user’s preferences with those of his/her nearby friends to present POI’s that are suitable to all of them. All data and rules are stored in the Sesame RDF triple store in order to be shared among various systems.


Semantic Web Ontologies Rules Context Location Based Services Points of Interest Preferences Group-Targeted Offers 


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  1. 1.
    Baldauf, M., Frohlich, P., Masuch, K., Grechenig, T.: Comparing viewing and filtering techniques for mobile urban exploration. Journal of LBS 5, 38–57 (2011)Google Scholar
  2. 2.
    Michael, K., Michael, M.G.: The social and behavioural implications of location based services. Journal of Location Based Services 5(3-4), 121–137 (2011)CrossRefGoogle Scholar
  3. 3.
    Roick, O., Heuser, S.: Location Based Social Networks – Definition, Current State of the Art and Research Agenda. Transactions in GIS 17(5), 763–784 (2013)Google Scholar
  4. 4.
    Zheng, Y., Xie, X., Ma, W.Y.: GeoLife: A Collaborative Social Networking Service among User. IEEE Data Eng. Bull. 33(2), 32–39 (2010)Google Scholar
  5. 5.
    Hosseini-Pozveh, M., Nematbakhsh, M., Movahhedinia, N.: A multidimensional approach for context-aware recommendation in mobile commerce. (IJCSIS) International Journal of Computer Science and Information Security 3(1) (2009)Google Scholar
  6. 6.
    Ilarri, S., lllarramendi, A., Mena, E., Sheth, A.: Semantics in Location-Based Services. IEEE Internet Computing 15(6), 10–14 (2011)CrossRefGoogle Scholar
  7. 7.
    Patkos, T., Bikakis, A., Antoniou, G., Papadopouli, M., Plexousakis, D.: A semantics-based framework for context-aware services: lessons learned and challenges. In: Indulska, J., Ma, J., Yang, L.T., Ungerer, T., Cao, J. (eds.) UIC 2007. LNCS, vol. 4611, pp. 839–848. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Giurca, A., Tylkowski, M., Muller, M.: RuleTheWeb!: Rule-based Adaptive User Experience. In: Proceedings of the RuleML2012@ECAI Challenge, at the 6th International Symposium on Rules, Montpellier, France, August 27-29. CEUR Workshop Proceedings, vol. 874 (2012)Google Scholar
  9. 9.
    Viktoratos, I., Tsadiras, A., Bassiliades, N.: A Rule Based Personalized Location Information System for the Semantic Web. In: Knuth, E., Neuhold, E.J. (eds.) Operating Systems 1982. LNCS, vol. 152, pp. 27–38. Springer, Heidelberg (1985)Google Scholar
  10. 10.
    Ciaramella, A., Cimino, M.G., Lazzerini, B., Marcelloni, F.: Situation-Aware Mobile Service Recommendation with Fuzzy Logic and Semantic Web. In: Ninth Int. Conference on Intelligent Systems Design and Applications. IEEE (2009)Google Scholar
  11. 11.
    García-Crespo, Á., López-Cuadrado, J.L., Colomo-Palacios, R., González Carrasco, I., Ruiz-Mezcua, B.: Sem-Fit: A semantic based expert system to provide recommendations in the tourism domain. Expert Systems with Applications 38 (2011)Google Scholar
  12. 12.
    Niforatos, E., Karapanos, E., Sioutas, S.: PLBSD: A platform for proactive location-based service discovery. Location Based Services Journal 6 (2012)Google Scholar
  13. 13.
    Armenatzoglou, N., et al.: FleXConf: A flexible conference assistant using context-aware notification services. In: Meersman, R., Herrero, P., Dillon, T. (eds.) OTM 2009 Workshops. LNCS, vol. 5872, pp. 108–117. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  14. 14.
    Viana, W., Filho, J.B., Gensel, J., Villanova-Oliver, M., Martin, H.: PhotoMap: From location and time to context-aware photo annotations. Journal of Location Based Services 2(3), 211–235 (2008)CrossRefGoogle Scholar
  15. 15.
    Serrano, D., Hervás, R., Bravo, J.: Telemaco: Context-aware System for Tourism Guiding based on Web 3.0 Technology. In: International Workshop on Contextual Computing and Ambient Intelligence in Tourism (2011)Google Scholar
  16. 16.
    Li, J., Wang, H., Khan, S.U.: A Semantics-based Approach to Large-Scale Mobile Social Networking. Mobile Networks and Applications 17(2), 192–205 (2012)CrossRefGoogle Scholar
  17. 17.
    Dell’Aglio, D., Celino, I., Cerizza, D.: Anatomy of a Semantic Web-enabled Recommender System. In: 9th Int. Semantic Web Conference on Proceedings of the 4th Int. Workshop Semantic Matchmaking and Resource Retrieval in the Semantic Web, Shanghai (2010)Google Scholar
  18. 18.
    Felfernig, A., Friedrich, G., Jannach, D., Zanker, M.: An Integrated Environment for the Development of Knowledge-Based Recommender Applications. Int. J. Electron. Commerce 11(2), 11–34 (2006)CrossRefGoogle Scholar
  19. 19.
    Ye, M., et al.: On the semantic annotation of places in location-based social networks. In: Proc.17th Int.Conf. ACM SIGKDD Knowledge Discovery& Data Mining, pp. 520–528 (2011)Google Scholar
  20. 20.
    Broekstra, J., Kampman, A., van Harmelen, F.: Sesame: An architecture for storing and querying RDF data and schema information. In: Lieberman, H., Fensel, D., Hendler, J., Wahlster, W. (eds.) Semantics for the WWW. MIT Press (2011)Google Scholar
  21. 21.
    Kontopoulos, E., Bassiliades, N., Antoniou, G.: Deploying Defeasible Logic Rule Bases for the Semantic Web. Data and Knowedge, Engineering 66(1), 116–146 (2008)CrossRefGoogle Scholar
  22. 22.
    Liang, S., Fodor, P., Wan, H., Kifer, M.: OpenRuleBench: An Analysis of the Performance of Rule Engines. In: WWW 2009(2009)Google Scholar
  23. 23.
    Sherman, G.: A Critical Analysis of XSLT Technology for XML Transformation. Senior Technical Report (2009)Google Scholar
  24. 24.
    Fields, D.K., Kolb, M.A., Bayern, S.: Web Development with Java Server Pages. Manning Publications (2001) ISBN:193011012XGoogle Scholar
  25. 25.
    Tavakol, M., Dennick, R.: Making sense of Cronbach’s alpha. International Journal of Medical Education 2, 53–55 (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Iosif Viktoratos
    • 1
  • Athanasios K. Tsadiras
    • 1
  • Nick Bassiliades
    • 2
  1. 1.Department of EconomicsAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Department of InformaticsAristotle University of ThessalonikiThessalonikiGreece

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