Hierarchical clustering based web service discovery

Huiying Gao, Susu Wang, Lily Sun, Fuxing Nian

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    15 Citations (Scopus)

    Abstract

    This paper presents a hierarchical clustering method for semantic Web service discovery. This method aims to improve the accuracy and efficiency of the traditional service discovery using vector space model. The Web service is converted into a standard vector format through the Web service description document. With the help of WordNet, a semantic analysis is conducted to reduce the dimension of the term vector and to make semantic expansion to meet the user’s service request. The process and algorithm of hierarchical clustering based semantic Web service discovery is discussed. Validation is carried out on the dataset.

    Original languageEnglish
    Title of host publicationService Science and Knowledge Innovation - 15th IFIP WG 8.1 International Conference on Informatics and Semiotics in Organisations, ICISO 2014, Proceedings
    EditorsKecheng Liu, Stephen R. Gulliver, Weizi Li, Changrui Yu
    PublisherSpringer New York LLC
    Pages281-291
    Number of pages11
    ISBN (Electronic)9783642553547
    DOIs
    Publication statusPublished - 2014
    Event15th IFIP WG 8.1 International Conference on Informatics and Semiotics in Organisations, ICISO 2014 - Shanghai, China
    Duration: 23 May 201424 May 2014

    Publication series

    NameIFIP Advances in Information and Communication Technology
    Volume426
    ISSN (Print)1868-4238
    ISSN (Electronic)1868-422X

    Conference

    Conference15th IFIP WG 8.1 International Conference on Informatics and Semiotics in Organisations, ICISO 2014
    Country/TerritoryChina
    CityShanghai
    Period23/05/1424/05/14

    Keywords

    • Hierarchical clustering
    • Semantic analysis
    • Service matching
    • Vector space model
    • Web service description
    • Web service discovery

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