A Big Data Analysis Framework for Model-Based Web User Behavior Analytics

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10360)


While basic Web analytics tools are widespread and provide statistics about website navigation, no approaches exist for merging such statistics with information about the Web application structure, content and semantics. Current analytics tools only analyze the user interaction at page level in terms of page views, entry and landing page, page views per visit, and so on. We show the advantages of combining Web application models with runtime navigation logs, at the purpose of deepening the understanding of users behaviour. We propose a model-driven approach that combines user interaction modeling (based on the IFML standard), full code generation of the designed application, user tracking at runtime through logging of runtime component execution and user activities, integration with page content details, generation of integrated schema-less data streams, and application of large-scale analytics and visualization tools for big data, by applying both traditional data visualization techniques and direct representation of statistics on visual models of the Web application.


User Interaction Object Management Group Page View User Navigation View Component 
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.


  1. 1.
  2. 2.
    Acerbis, R., Bongio, A., Brambilla, M., Butti, S.: Model-driven development based on omg’s ifml with webratio web and mobile platform. In: Cimiano, P., Frasincar, F., Houben, G.-J., Schwabe, D. (eds.) ICWE 2015. LNCS, vol. 9114, pp. 605–608. Springer, Cham (2015). doi: 10.1007/978-3-319-19890-3_39 CrossRefGoogle Scholar
  3. 3.
    Acerbis, R., Bongio, A., Brambilla, M., Butti, S.: Model-driven development of cross-platform mobile applications with WebRatio and IFML. In: 2nd ACM International Conference on Mobile Software Engineering and Systems, MOBILESoft 2015, Florence, Italy, 16–17 May 2015, pp. 170–171 (2015).
  4. 4.
    Agosti, M., Crivellari, F., Di Nunzio, G.M.: Web log analysis: a review of a decade of studies about information acquisition, inspection and interpretation of user interaction. Data Min. Knowl. Discov. 24(3), 663–696 (2012)CrossRefGoogle Scholar
  5. 5.
    Ameller, D., Franch, X., Gómez, C., Araujo, J., Svensson, R.B., Biffl, S., Cabot, J., Cortellessa, V., Daneva, M., Fernández, D.M., et al.: Handling non-functional requirements in model-driven development: an ongoing industrial survey. In: 2015 IEEE 23rd International Requirements Engineering Conference (RE), pp. 208–213. IEEE (2015)Google Scholar
  6. 6.
    Amyot, D., Mussbacher, G.: User requirements notation: the first ten years, the next ten years. J. Softw. 6(5), 747–768 (2011)CrossRefGoogle Scholar
  7. 7.
    Baresi, L., Garzotto, F., Paolini, P.: From web sites to web applications: new issues for conceptual modeling. In: Liddle, S.W., Mayr, H.C., Thalheim, B. (eds.) ER 2000. LNCS, vol. 1921, pp. 89–100. Springer, Heidelberg (2000). doi: 10.1007/3-540-45394-6_9 CrossRefGoogle Scholar
  8. 8.
    Brambilla, M., Fraternali, P.: Interaction Flow Modeling Language Model-Driven UI Engineering of Web and Mobile Apps with IFML. The OMG Press, Morgan-Kaufmann, Burlington (2014)Google Scholar
  9. 9.
    Brambilla, M., Mauri, A., Umuhoza, E.: Extending the interaction flow modeling language (IFML) for model driven development of mobile applications front end. In: Awan, I., Younas, M., Franch, X., Quer, C. (eds.) MobiWIS 2014. LNCS, vol. 8640, pp. 176–191. Springer, Cham (2014). doi: 10.1007/978-3-319-10359-4_15 Google Scholar
  10. 10.
    Breu, R., Chimiak-Opoka, J.: Towards systematic model assessment. In: Akoka, J., Liddle, S.W., Song, I.-Y., Bertolotto, M., Comyn-Wattiau, I., Heuvel, W.-J., Kolp, M., Trujillo, J., Kop, C., Mayr, H.C. (eds.) ER 2005. LNCS, vol. 3770, pp. 398–409. Springer, Heidelberg (2005). doi: 10.1007/11568346_43 CrossRefGoogle Scholar
  11. 11.
    Burby, J., Brown, A., et al.: Web analytics definitions (2007)Google Scholar
  12. 12.
    Cicchetti, A., Ruscio, D., Eramo, R., Maccarrone, F., Pierantonio, A.: beContent: a model-driven platform for designing and maintaining web applications. In: Gaedke, M., Grossniklaus, M., Díaz, O. (eds.) ICWE 2009. LNCS, vol. 5648, pp. 518–522. Springer, Heidelberg (2009). doi: 10.1007/978-3-642-02818-2_52 CrossRefGoogle Scholar
  13. 13.
    Conallen, J.: Building Web Applications with UML. Addison Wesley, Boston (2002)zbMATHGoogle Scholar
  14. 14.
    Cordeiro, L., Fischer, B.: Verifying multi-threaded software using SMT-based context-bounded model checking. In: Proceedings of the 33rd International Conference on Software Engineering, ICSE 2011, NY, USA, pp. 331–340 (2011).
  15. 15.
    Di Rocco, J., Di Ruscio, D., Iovino, L., Pierantonio, A.: Mining metrics for understanding metamodel characteristics. In: Proceedings of the 6th International Workshop on Modeling in Software Engineering, MiSE 2014, NY, USA, pp. 55–60 (2014).
  16. 16.
    Di Ruscio, D., Pelliccione, P.: A model-driven approach to detect faults in FOSS systems. J. Softw. Evol. Proc. 27(4), 294–318 (2015). CrossRefGoogle Scholar
  17. 17.
    Fraternali, P., Lanzi, P.L., Matera, M., Maurino, A.: Model-driven web usage analysis for the evaluation of web application quality. J. Web Eng. 3(2), 124–152 (2004). Google Scholar
  18. 18.
    Gérard, S., Dumoulin, C., Tessier, P., Selic, B.: 19 Papyrus: a UML2 tool for domain-specific language modeling. In: Giese, H., Karsai, G., Lee, E., Rumpe, B., Schätz, B. (eds.) MBEERTS 2007. LNCS, vol. 6100, pp. 361–368. Springer, Heidelberg (2010). doi: 10.1007/978-3-642-16277-0_19 CrossRefGoogle Scholar
  19. 19.
    Giese, H., Tichy, M., Burmester, S., Schäfer, W., Flake, S.: Towards the compositional verification of real-time uml designs. SIGSOFT Softw. Eng. Notes 28(5), 38–47 (2003). CrossRefGoogle Scholar
  20. 20.
    Gómez, J., Cachero, C., Pastor, O., Pastor, O.: Conceptual modeling of device-independent web applications, pp. 26–39 (2001)Google Scholar
  21. 21.
    Groenewegen, D.M., Hemel, Z., Kats, L.C.L., Visser, E.: Webdsl: a domain-specific language for dynamic web applications. In: OOPSLA Companion, pp. 779–780 (2008)Google Scholar
  22. 22.
    Ledford, J.L., Teixeira, J., Tyler, M.E.: Google Analytics. Wiley, New York (2011)Google Scholar
  23. 23.
    Mecca, G., Merialdo, P., Atzeni, P., Crescenzi, V., Crescenzi, V.: The (short) araneus guide to web-site development. In: WebDB (Informal Proceedings), pp. 13–18 (1999)Google Scholar
  24. 24.
    (OMG), O.M.G., Brambilla, M., Fraternali, P.: IFML: Interaction Flow Modeling Language.
  25. 25.
    Salini, A., Malavolta, I., Rossi, F.: Leveraging web analytics for automatically generating mobile navigation models. In: 2016 IEEE International Conference on Mobile Services (MS), pp. 103–110. IEEE (2016)Google Scholar
  26. 26.
    Schwabe, D., Rossi, G., Rossi, G.: The object-oriented hypermedia design model, pp. 45–46 (1995)Google Scholar
  27. 27.
    Syriani, E., Vangheluwe, H., Mannadiar, R., Hansen, C., Van Mierlo, S., Ergin, H.: Atompm: a web-based modeling environment. In: Demos/Posters/StudentResearch@ MoDELS, pp. 21–25 (2013)Google Scholar
  28. 28.
    Umuhoza, E., Brambilla, M., Cabot, J., Bongio, A., et al.: Automatic code generation for cross-platform, multi-device mobile apps: some reflections from an industrial experience. In: Proceedings of the 3rd International Workshop on Mobile Development Lifecycle, pp. 37–44. ACM (2015)Google Scholar
  29. 29.
    Vdovják, R., Frăsincar, F., Houben, G.J., Barna, P.: Engineering semantic web information systems in Hera. J. Web Eng. 1(1–2), 3–26 (2003)zbMATHGoogle Scholar
  30. 30.
    Völter, M., Benz, S., Dietrich, C., Engelmann, B., Helander, M., Kats, L.C.L., Visser, E., Wachsmuth, G.: DSL Engineering - Designing, Implementing and Using Domain-Specific Languages. (2013).
  31. 31.
    Waisberg, D., Kaushik, A.: Web analytics 2.0: empowering customer centricity. Original Search Engine Mark. J. 2(1), 5–11 (2009)Google Scholar
  32. 32.
    Winckler, M., Pontico, F.: A model-driven architecture for logging navigation. In: Workshop on Logging Traces of Web Activity: Workshop on the Mechanics of Data Collection, Co-located with 15th International World Wide Web Conference (WWW 2006), Edinburgh, Scotland (2006)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Politecnico di MilanoMilanItaly

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