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VsLattice: A vector-based conceptual index structure for web service retrieval

Author

Listed:
  • Dunlu Peng

    (University of Shanghai for Science and Technology)

  • Xiaoling Wang

    (Fudan University)

  • Aoying Zhou

    (Fudan University)

Abstract

With the rising adoption of web services, effective management of web services becomes a critical issue in making the paradigm of service-oriented computing more practical. In this paper, a novel structure, called Vector-based service Lattice ( VsLattice), is devised to index web services in a semantic way. Each web service is modeled as a group of Service Operation Vectors (SOVs) in the vector space, and each SOV represents an operation provided by the service. The web services, SOVs and the relationship between web services and SOVs form the Conceptual Indexing Context (CIC) of a given service collection. In the CIC, web services that provide similar operations (functions) are conceptually indexed by the same Operation Vector Concepts (OVCs). The underlying relationships among the OVCs are captured with the VsLattice, which is constructed by adopting the traditional concept lattice in a CIC. By taking advantage of the information obtained from the VsLattice, a new representation of SOV is devised. Based on this representation, a novel service retrieval model and the implemental system are developed to retrieve web services efficiently. The performance and retrieving quality of the proposed approach has been evaluated through a series of experiments.

Suggested Citation

  • Dunlu Peng & Xiaoling Wang & Aoying Zhou, 2007. "VsLattice: A vector-based conceptual index structure for web service retrieval," Information Systems Frontiers, Springer, vol. 9(4), pages 423-437, September.
    • Handle: RePEc:spr:infosf:v:9:y:2007:i:4:d:10.1007_s10796-007-9044-5
    DOI: 10.1007/s10796-007-9044-5
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    Cited by:

    1. Claudia Diamantini & Domenico Potena & Emanuele Storti, 2013. "A virtual mart for knowledge discovery in databases," Information Systems Frontiers, Springer, vol. 15(3), pages 447-463, July.
    2. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.

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