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QoS Browsing for Web Service Selection

  • Chen Ding
  • Preethy Sambamoorthy
  • Yue Tan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5900)

Abstract

In most of current research works on Quality of Service (QoS) based web service selection, searching is usually the dominant way to find the desired services. However, sometimes, requestors may not have the knowledge of the available QoS attributes and their value ranges in the registry, or they may only have vague QoS requirements. Under this situation, we believe that browsing is a more appropriate way to help the QoS-based service selection process. In this paper, we propose an interactive QoS browsing mechanism to first show an overview of the QoS value distribution to requestors and then gradually present more and more detailed views on some requestor interested value ranges. We find that interval data (or more generally symbolic data) is a more proper type to represent the QoS value, compared with the single valued numerical data. So we use interval clustering algorithms to implement our browsing system. The experiment compares the performance of using different distance measures and shows the effectiveness of the interval clustering algorithm we use. We also use a sample data set to illustrate the interactive QoS browsing process.

Keywords

Interval Data Service Selection Cluster Prototype Symbolic Data Analysis Dynamic Cluster Algorithm 
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

  • Chen Ding
    • 1
  • Preethy Sambamoorthy
    • 1
  • Yue Tan
    • 2
  1. 1.Department of Computer ScienceRyerson UniversityCanada
  2. 2.School of SoftwareTsinghua UniversityChina

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