Rule-Based Knowledge Management in Social Threat Monitor

  • Mateusz Baran
  • Antoni Ligęza
Part of the Communications in Computer and Information Science book series (CCIS, volume 368)


Social Threat Monitor (STM) is a Web system incorporating a relational database and GIS component for enregistration of user provided data on threats. In contrast to typical Crime Mapping Systems — where only authorized services, such as Police, are allowed and responsible for selective threat reporting — in case of STM all registered citizens can input threat data of interest. Registered data can be spatially visualized allowing easy browsing of reports. Wide, distributed and unlimited access makes this kind of service a new quality on the way to threat monitoring and safety improvement. However, due to a huge volumes of complex, multi-aspect data, automated knowledge management appears indispensable. In this paper a Rule-Based System for report processing and knowledge management is proposed. A new taxonomy of rules for complex knowledge management tasks is put forward. The rules are used to assess report admissibility, access restriction, perform basic processing and threat inference. Special ECA-type rules provide immediate reaction to dangerous situations and run statistical analysis of gathered data. The rules are written in Prolog.


Knowledge Management Rule-Based Systems GIS INDECT 


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  1. 1.
    Adrian, W.T., Bobek, S., Nalepa, G.J., Kaczor, K., Kluza, K.: How to reason by HeaRT in a semantic knowledge-based wiki. In: Proceedings of the 23rd IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2011, Boca Raton, Florida, USA, pp. 438–441 (November 2011),
  2. 2.
    Adrian, W.T., Ciężkowski, P., Kaczor, K., Ligęza, A., Nalepa, G.J.: Web-based knowledge acquisition and management system supporting collaboration for improving safety in urban environment. In: Dziech, A., Czyżewski, A. (eds.) MCSS 2012. CCIS, vol. 287, pp. 1–12. Springer, Heidelberg (2012), CrossRefGoogle Scholar
  3. 3.
    Baki, B., Bouzid, M., Ligęza, A., Mouaddib, A.I.: A centralized planning technique with temporal constraints and uncertainty for multi-agent systems. Journal of Experimental and Theoretical Artificial Intelligence 18(3), 331–364 (2006)CrossRefGoogle Scholar
  4. 4.
    Caballé, S., Daradoumis, T., Xhafa, F., Conesa, J.: Enhancing knowledge management in online collaborative learning. International Journal of Software Engineering and Knowledge Engineering 20(4), 485–497 (2010)CrossRefGoogle Scholar
  5. 5.
    Coenen, F., et al.: Validation and verification of knowledge-based systems: report on eurovav99. The Knowledge Engineering Review 15(2), 187–196 (2000)CrossRefGoogle Scholar
  6. 6.
    Kluza, K., Maślanka, T., Nalepa, G.J., Ligęza, A.: Proposal of representing BPMN diagrams with XTT2-based business rules. In: Brazier, F.M., Nieuwenhuis, K., Pavlin, G., Warnier, M., Badica, C. (eds.) Intelligent Distributed Computing V. Proceedings of the 5th International Symposium on Intelligent Distributed Computing – IDC 2011. SCI, vol. 382, pp. 243–248. Springer, Heidelberg (2011), Google Scholar
  7. 7.
    Levine, N.: Crime mapping and the crimestat program. Geographical Analysis 38(1), 41–56 (2006), CrossRefGoogle Scholar
  8. 8.
    Liebowitz, J. (ed.): The Handbook of Applied Expert Systems. CRC Press, Boca Raton (1998)MATHGoogle Scholar
  9. 9.
    Ligęza, A.: Expert systems approach to decision support. European Journal of Operational Research 37(1), 100–110 (1988)CrossRefGoogle Scholar
  10. 10.
    Ligęza, A.: Intelligent data and knowledge analysis and verification; towards a taxonomy of specific problems. In: Vermesan, A., Coenen, F. (eds.) Validation and Verification of Knowledge Based Systems: Theory, Tools and Practice, pp. 313–325. Kluwer Academic Publishers (1999)Google Scholar
  11. 11.
    Ligęza, A.: Logical Foundations for Rule-Based Systems. Springer, Heidelberg (2006)MATHGoogle Scholar
  12. 12.
    Ligęza, A., Adrian, W.T., Ernst, S., Nalepa, G.J., Szpyrka, M., Czapko, M., Grzesiak, P., Krzych, M.: Prototypes of a web system for citizen provided information, automatic knowledge extraction, knowledge management and GIS integration. In: Dziech, A., Czyżewski, A. (eds.) MCSS 2011. CCIS, vol. 149, pp. 268–276. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  13. 13.
    Ligęza, A., Adrian, W.T., Kaczor, K., Nalepa, G.J., Ciężkowski, P., Żywioł, M., Grzesiak, P.: Web system for citizen provided information, automatic knowledge extraction, knowledge management and GIS integration. INDECT D4.14 technical reportGoogle Scholar
  14. 14.
    Ligęza, A., Adrian, W.T., Kaczor, K., Nalepa, G.J., Ciężkowski, P., Żywioł, M., Grzesiak, P.: Web system for citizen provided information, automatic knowledge extraction, knowledge management and GIS integration. INDECT D9.30 technical reportGoogle Scholar
  15. 15.
    Ligęza, A., Ernst, S., Nowaczyk, S., Nalepa, G.J., Szpyrka, M., Furmańska, W.T., Czapko, M., Grzesiak, P., Kałuża, M., Krzych, M.: Towards enregistration of threats in urban environments: practical consideration for a GIS-enabled web knowledge acquisition system. In: Dańda, J., Derkacz, J., Głowacz, A. (eds.) MCSS 2010: IEEE International Conference on Multimedia Communications, Services and Security, Kraków, Poland, May 6-7, pp. 152–158 (2010)Google Scholar
  16. 16.
    Ligęza, A., Nalepa, G.J.: A study of methodological issues in design and development of rule-based systems: proposal of a new approach. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 1(2), 117–137 (2011)CrossRefGoogle Scholar
  17. 17.
    Nalepa, G.J., Bobek, S., Ligęza, A., Kaczor, K.: HalVA - rule analysis framework for XTT2 rules. In: Bassiliades, N., Governatori, G., Paschke, A. (eds.) RuleML 2011 - Europe. LNCS, vol. 6826, pp. 337–344. Springer, Heidelberg (2011), CrossRefGoogle Scholar
  18. 18.
    Nalepa, G.J.: PlWiki – A generic semantic wiki architecture. In: Nguyen, N.T., Kowalczyk, R., Chen, S.-M. (eds.) ICCCI 2009. LNCS, vol. 5796, pp. 345–356. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  19. 19.
    Nalepa, G.J., Kluza, K.: UML representation for rule-based application models with XTT2-based business rules. International Journal of Software Engineering and Knowledge Engineering (IJSEKE) 22(4), 485–524 (2012), CrossRefGoogle Scholar
  20. 20.
    Nalepa, G.J., Ligęza, A.: Designing reliable Web security systems using rule-based systems approach. In: Menasalvas, E., Segovia, J., Szczepaniak, P.S. (eds.) AWIC 2003. LNCS (LNAI), vol. 2663, pp. 124–133. Springer, Heidelberg (2003)Google Scholar
  21. 21.
    Nalepa, G.J., Ligęza, A.: Conceptual modelling and automated implementation of rule-based systems. In: Software Engineering: Evolution and Emerging Technologies, Frontiers in Artificial Intelligence and Applications, vol. 130, pp. 330–340. IOS Press, Amsterdam (2005)Google Scholar
  22. 22.
    Nalepa, G.J., Ligęza, A.: HeKatE methodology, hybrid engineering of intelligent systems. International Journal of Applied Mathematics and Computer Science 20(1), 35–53 (2010)CrossRefGoogle Scholar
  23. 23.
    Nalepa, G.J., Ligęza, A., Kaczor, K.: Formalization and modeling of rules using the XTT2 method. International Journal on Artificial Intelligence Tools 20(6), 1107–1125 (2011)CrossRefGoogle Scholar
  24. 24.
    Open Geospatial Consortium: OpenGIS geography markup language (GML) implementation specification, version 2.1.2,

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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mateusz Baran
    • 1
  • Antoni Ligęza
    • 1
  1. 1.AGH University of Science and TechnologyKrakowPoland

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