• DocumentCode
    2126145
  • Title

    Using semantic similarity model to improve OGC web services matching accuracy

  • Author

    Miao, Lizhi ; Zhou, Ya ; Cheng, Wenchao ; Guo, Jing

  • Author_Institution
    College of Geographical and Biological Information, Nanjing University of Posts and Telecommunications, China
  • fYear
    2015
  • fDate
    20-24 July 2015
  • Firstpage
    217
  • Lastpage
    220
  • Abstract
    In order to seek out available service from massive geographic information services with high accuracy and satisfy the needs of service users, this paper takes advantage of the characteristics of metadata documents of OGC geographic information services, extracting many description vocabularies from metadata description files according to different tags´ weight. Then, a semantic similarity measurement model is proposed to figure out the semantic similarity between the search keyword and OGC Web Service described by semantic distance similarity, semantic structure similarity and attribute information similarity. Using the above model, several experiments are implemented. The results show that: 1. the computing mode of the integrated semantic similarity proposed in this paper is in line with the public cognition and the expert evaluation. 2. comparing with the keyword-based search method, the semantic similarity model could increase recall ratio over 40%, up to 90%; and increase precision over 6%, up to 90%.
  • Keywords
    Computational modeling; Information services; Minerals; Ontologies; Rivers; Semantics; Vocabulary; OGC web service; geographic ontology; semantic search; semantic similarity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Agro-Geoinformatics (Agro-geoinformatics), 2015 Fourth International Conference on
  • Conference_Location
    Istanbul, Turkey
  • Type

    conf

  • DOI
    10.1109/Agro-Geoinformatics.2015.7248120
  • Filename
    7248120