Web Services Reputation Assessment Using a Hidden Markov Model

  • Zaki Malik
  • Ihsan Akbar
  • Athman Bouguettaya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5900)


We present an approach for reputation assessment in service-oriented environments. We define key metrics to aggregate the feedbacks of different raters, for assessing a service provider’s reputation. In situations where rater feedbacks are not readily available, we use a Hidden Markov Models (HMM) to predict the reputation of a service provider. HMMs have proven to be suitable in numerous research areas for modelling dynamic systems. We propose to emulate the success of such systems for evaluating service reputations to enable trust-based interactions with and amongst Web services. The experiment details included in this paper show the applicability of the proposed HMM-based reputation assessment model.


Service Provider Hide Markov Model Bayesian Information Criterion Reputation System Service Consumer 
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 2009

Authors and Affiliations

  • Zaki Malik
    • 1
  • Ihsan Akbar
    • 2
  • Athman Bouguettaya
    • 3
  1. 1.Department of Computer ScienceWayne State UniversityDetroitUSA
  2. 2.Department of Electrical EngineeringVirginia Tech BlacksburgUSA
  3. 3.CSIRO, ICT CenterCanberraAustralia

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