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WS-Finder: A Framework for Similarity Search of Web Services

  • Jiangang Ma
  • Quan Z. Sheng
  • Kewen Liao
  • Yanchun Zhang
  • Anne H. H. Ngu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7636)

Abstract

Most existing Web service search engines employ keyword search over databases, which computes the distance between the query and the Web services over a fixed set of features. Such an approach often results in incompleteness of search results. The Earth Mover’s Distance (EMD) has been successfully used in multimedia databases due to its ability to capture the differences between two distributions. However, calculating EMD is computationally intensive. In this paper, we present a novel framework called WS-Finder, which improves the existing keyword-based search techniques for Web services. In particular, we employ EMD for many-to-many partial matching between the contents of the query and the service attributes. We also develop a generalized minimization lower bound as a new EMD filter for partial matching. This new EMD filter is then combined to a k-NN algorithm for producing complete top-k search results. Furthermore, we theoretically and empirically show that WS-Finder is able to produce query answers effectively and efficiently.

Keywords

Similarity Search Range Query Partial Match Word Sequence Multimedia Database 
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 2012

Authors and Affiliations

  • Jiangang Ma
    • 1
  • Quan Z. Sheng
    • 1
  • Kewen Liao
    • 1
  • Yanchun Zhang
    • 2
  • Anne H. H. Ngu
    • 3
  1. 1.School of Computer ScienceThe University of AdelaideAustralia
  2. 2.School of Engineering and ScienceVictoria UniversityAustralia
  3. 3.Department of Computer ScienceTexas State UniversityUSA

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