Automatic Composition of Form-Based Services in a Context-Aware Personal Information Space

  • Rania Khéfifi
  • Pascal Poizat
  • Fatiha Saïs
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8274)


Personal Information Spaces (PIS) help in structuring, storing, and retrieving personal information. Still, it is the users’ duty to sequence the basic steps in different online procedures, and to fill out the corresponding forms with personal information, in order to fulfill some objectives. We propose an extension for PIS that assists users in achieving this duty. We perform a composition of form-based services in order to reach objectives expressed as workflow of capabilities. Further, we take into account that user personal information can be contextual and that the user may have personal information privacy policies. Our solution is based on graph planning and is fully tool-supported.


Service Composition Ontologies Contextual Data Personal Information Privacy Graph Planning 


  1. 1.
    Anand, P., Vladimir, K., Lalana, K., Anupam, J.: Enforcing policies in pervasive environments. In: Proc. of MobiQuitous (2004)Google Scholar
  2. 2.
    Bartalos, P., Bieliková, M.: Automatic Dynamic Web Service Composition: A Survey and Problem Formalization. Computing and Informatics 30(4), 793–827 (2012)Google Scholar
  3. 3.
    Blum, A., Furst, M.L.: Fast Planning Through Planning Graph Analysis. Artificial Intelligence 90(1-2), 281–300 (1997)CrossRefzbMATHGoogle Scholar
  4. 4.
    Dulay, N., Damianou, N., Lupu, E.C., Sloman, M.: A policy language for the management of distributed agents. In: Wooldridge, M.J., Weiß, G., Ciancarini, P. (eds.) AOSE 2001. LNCS, vol. 2222, pp. 84–100. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  5. 5.
    Hutter, D., Volkamer, M.: Information Flow Control to Secure Dynamic Web Service Composition. In: Clark, J.A., Paige, R.F., Polack, F.A.C., Brooke, P.J. (eds.) SPC 2006. LNCS, vol. 3934, pp. 196–210. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Khéfifi, R., Poizat, P., Saïs, F.: Modeling and Querying Context-Aware Personal Information Spaces. In: Liddle, S.W., Schewe, K.-D., Tjoa, A.M., Zhou, X. (eds.) DEXA 2012, Part II. LNCS, vol. 7447, pp. 103–110. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  7. 7.
    Kiepusewski, B.: Expressiveness and suitability of languages for control flow modelling in workflows. Queensland University of Technology, Brisbane (2003)Google Scholar
  8. 8.
    Marconi, A., Pistore, M.: Synthesis and Composition of Web Services. In: Bernardo, M., Padovani, L., Zavattaro, G. (eds.) SFM 2009. LNCS, vol. 5569, pp. 89–157. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  9. 9.
    Mostéfaoui, S.K., Hirsbrunner, B.: Towards a Context-Based Service Composition Framework. In: Proc. of ICWS (2003)Google Scholar
  10. 10.
    Mrissa, M., Benslimane, D., Maamar, Z., Ghedira, C.: Towards a semantic- and context-based approach for composing web services. IJWGS 1(3/4), 268–286 (2005)CrossRefGoogle Scholar
  11. 11.
    Poizat, P., Yan, Y.: Adaptive Composition of Conversational Services through Graph Planning Encoding. In: Margaria, T., Steffen, B. (eds.) ISoLA 2010, Part II. LNCS, vol. 6416, pp. 35–50. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  12. 12.
    Russell, S.J., Norvig, P., Canny, J.F., Malik, J.M., Edwards, D.D.: Artificial Intelligence: A Modern Approach. Prentice hall, Englewood Cliffs (1995)Google Scholar
  13. 13.
    Sheshagiri, M., Sadeh, N., Gandon, F.: Using Semantic Web Services for Context-Aware Mobile Applications. In: Proc. of MobiSys (2004)Google Scholar
  14. 14.
    Yan, Y., Poizat, P., Zhao, L.: Repair vs. Recomposition for Broken Service Compositions. In: Maglio, P.P., Weske, M., Yang, J., Fantinato, M. (eds.) ICSOC 2010. LNCS, vol. 6470, pp. 152–166. Springer, Heidelberg (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Rania Khéfifi
    • 1
  • Pascal Poizat
    • 2
  • Fatiha Saïs
    • 1
  1. 1.LRI, CNRSParis Sud UniversityFrance
  2. 2.LIP6, CNRSParis Ouest UniversityFrance

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