Toward Approximate GML Retrieval Based on Structural and Semantic Characteristics

  • Joe Tekli
  • Richard Chbeir
  • Fernando Ferri
  • Patrizia Grifoni
Conference paper

DOI: 10.1007/978-3-642-13911-6_2

Volume 6189 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Tekli J., Chbeir R., Ferri F., Grifoni P. (2010) Toward Approximate GML Retrieval Based on Structural and Semantic Characteristics. In: Benatallah B., Casati F., Kappel G., Rossi G. (eds) Web Engineering. ICWE 2010. Lecture Notes in Computer Science, vol 6189. Springer, Berlin, Heidelberg

Abstract

GML is emerging as the new standard for representing geographic information in GISs on the Web, allowing the encoding of structurally and semantically rich geographic data in self describing XML-based geographic entities. In this study, we address the problem of approximate querying and ranked results for GML data and provide a method for GML query evaluation. Our method consists of two main contributions. First, we propose a tree model for representing GML queries and data collections. Then, we introduce a GML retrieval method based on the concept of tree edit distance as an efficient means for comparing semi-structured data. Our approach allows the evaluation of both structural and semantic similarities in GML data, enabling the user to tune the querying process according to her needs. The user can also choose to perform either template querying, taking into account all elements in the query and data trees, or minimal constraint querying, considering only those elements required by the query (disregarding additional data elements), in the similarity evaluation process. An experimental prototype was implemented to test and validate our method. Results are promising.

Keywords

GML Search Ranked Retrieval Structural & Semantic Similarity GIS 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Joe Tekli
    • 1
  • Richard Chbeir
    • 1
  • Fernando Ferri
    • 2
  • Patrizia Grifoni
    • 2
  1. 1.LE2I Laboratory UMR-CNRSUniversity of BourgogneDijon CedexFrance
  2. 2.IRPPS-CNRRomaItaly