Wisdom-Aware Computing: On the Interactive Recommendation of Composition Knowledge

  • Soudip Roy Chowdhury
  • Carlos Rodríguez
  • Florian Daniel
  • Fabio Casati
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6568)


We propose to enable and facilitate the development of service-based development by exploiting community composition knowledge, i.e., knowledge that can be harvested from existing, successful mashups or service compositions defined by other and possibly more skilled developers (the community or crowd) in a same domain. Such knowledge can be used to assist less skilled developers in defining a composition they need, allowing them to go beyond their individual capabilities. The assistance comes in the form of interactive advice, as we aim at supporting developers while they are defining their composition logic, and it adjusts to the skill level of the developer. In this paper we specifically focus on the case of process-oriented, mashup-like applications, yet the proposed concepts and approach can be generalized and also applied to generic algorithms and procedures.


Association Rule Service Composition Frequent Itemset Mining Sequential Pattern Mining Modeling Canvas 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Soudip Roy Chowdhury
    • 1
  • Carlos Rodríguez
    • 1
  • Florian Daniel
    • 1
  • Fabio Casati
    • 1
  1. 1.University of TrentoPovoItaly

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