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Web Service Composition with User Preferences

  • Naiwen Lin
  • Ugur Kuter
  • Evren Sirin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5021)

Abstract

In Web Service Composition (WSC) problems, the composition process generates a composition (i.e., a plan) of atomic services, whose execution achieves some objectives on the Web. Existing research on Web service composition generally assumed that these objectives are absolute; i.e., the service-composition algorithms must achieve all of them in order to generate successful outcomes; otherwise, the composition process fails altogether. The most straightforward example is the use of OWL-S process models that specifically tell a composition algorithm how to achieve a functionality on the Web. However, in many WSC problems, it is also desirable to achieve users’ preferences that are not absolute objectives; instead, a solution composition generated by a WSC algorithm must satisfy those preferences as much as possible. In this paper, we first describe a way to augment Web Service Composition process, where services are described as OWL-S process models, with qualitative user preferences. We achieve this by mapping a given set of process models and preferences into a planning language for representing Hierarchical Task Networks (HTNs). We then present SCUP, our new WSC planning algorithm that performs a best-first search over the possible HTN-style task decompositions, by heuristically scoring those decompositions based on ontological reasoning over the input preferences. Finally, we discuss our experimental results on SCUP.

Keywords

User Preference Planning Language Task Network Ontological Reasoning Hierarchical Task Network 
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 2008

Authors and Affiliations

  • Naiwen Lin
    • 1
  • Ugur Kuter
    • 1
  • Evren Sirin
    • 2
  1. 1.Department of Computer Science and Institute for Advanced Computer StudiesUniversity of MarylandCollege ParkUSA
  2. 2.Clark & ParsiaLLCWashingtonUSA

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