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iRank: Ranking Geographical Information by Conceptual, Geographic and Topologic Similarity

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GeoSpatial Semantics (GeoS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5892))

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Abstract

Geographic Information Ranking consists of measuring if a document (answer) is relevant to a spatial query. It is done by comparing characteristics in common between document and query. The most popular approaches compare just one aspect of geographical data (geographic properties, topology, among others). It limits the assessment of document relevance. Nevertheless, it can be improved when key characteristics of geographical objects are considered in the ranking (1) geographical attributes, (2) topological relations, and (3) geographical concepts. In this paper, we outline iRank a method that integrates these three aspects to rank a document. Ourapproach evaluates documents from three sources of information: GeoOntologies, dictionaries, and topology files. Relevance is measured according to three stages. In the first stage, the relevance is computed by processing concepts; in second stage relevance is calculated using geographic attributes. In the last stage, the relevance is measured by computing topologic relations. Thus, the main contribution of iRank is show that integration of three ranking criteria is better than when they are used in separate way.

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Authors and Affiliations

  1. Interdisciplinary Professional Unit in Engineering and Advanced Tecnologies, National Polytechnic Institute, Av. IPN No. 2580, Col. Barrio la Laguna Ticomán, Gustavo A. Madero, CP. 07340, México, D.F.

    Felix Mata

Authors
  1. Felix Mata
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Editor information

Editors and Affiliations

  1. Department of Geography, The Pennsylvania State University, University Park, 16802, PA, USA

    Krzysztof Janowicz

  2. Department of Geography, University of California, Santa Barbara, 93106, CA, USA

    Martin Raubal

  3. Centro de Investigacion en Computacion, National Polytechnic Institute, 07738, Mexico City, Mexico

    Sergei Levashkin

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Mata, F. (2009). iRank: Ranking Geographical Information by Conceptual, Geographic and Topologic Similarity. In: Janowicz, K., Raubal, M., Levashkin, S. (eds) GeoSpatial Semantics. GeoS 2009. Lecture Notes in Computer Science, vol 5892. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10436-7_10

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  • DOI: https://doi.org/10.1007/978-3-642-10436-7_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10435-0

  • Online ISBN: 978-3-642-10436-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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