• DocumentCode
    1993969
  • Title

    Ontology-based retrieval of geographic information

  • Author

    Liu, Wei ; Gu, Hehe ; Peng, Chunmin ; Cheng, Dayu

  • Author_Institution
    Jiangsu Key Lab. of Resources & Environ. Inf. Eng., China Univ. of Min. & Technol., Xuzhou, China
  • fYear
    2010
  • fDate
    18-20 June 2010
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In the era of information explosion, information retrieval has become a bottleneck in information sharing and integration. However currently, the existing information retrieval methods are mainly based on keywords matching, which can not fully take advantage of the information context and potential knowledge. Although in the later researches, Geo-ontology has been used to enrich geospatial objects with semantic information which could be very helpful in the geospatial information retrieval, these researches have rarely considered the key feature of geospatial information-the complex spatial relationship. The researches focused on the general concept and primarily from the perspective of vocabulary describe the geographic information, which can not be used to describe the spatial relationship of geographic information and lack of support for retrieval of spatial relationship of geographic information. In this paper, we propose a new approach for geographic information retrieval, we have established the topology and direction and distance spatial relation of geographic information. Firstly, we analysis the shortcomings of current geographic information retrieval methods, and use a case to illustrate the shortcomings of current retrieval methods. Secondly, we analysis the spatial properties and non-spatial properties of semantic relation, and proposed that uses to describe geographic information of spatial relations of Attribute Relational Graph-ARG. Thirdly, according to the reference ontology, using Geo-ontology Building Algorithm-GOBA to build the geographic ontology instance. Finally, take the DALIAN Bay land utilization ontology as the example to show the availability of this method. We have also analysis the approach´s merit and deficiency in the conclusions part.
  • Keywords
    geographic information systems; graph theory; information retrieval; ontologies (artificial intelligence); Geo-ontology building algorithm-GOBA; attribute relational graph-ARG; geospatial information retrieval methods; information integration; information sharing; ontology-based retrieval; Buildings; Feature extraction; Geospatial analysis; Lakes; OWL; Ontologies; Semantics; Attribute Relational Graph-ARG; Geo-Ontology Building Algorithm-GOBA; geo-ontology; geographic information retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoinformatics, 2010 18th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-7301-4
  • Type

    conf

  • DOI
    10.1109/GEOINFORMATICS.2010.5567612
  • Filename
    5567612