Advertisement

Syntactic Rules of Spatial Relations in Natural Language

  • Shaonan Zhu
  • Xueying Zhang
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 236)

Abstract

Spatial relations are the main part of geographical information in natural language. Their extraction and semantic interpretation play a significant role in bridging the gap between geographical information system and natural language. Normally spatial relations are described with certain spatial terms and syntactic rules in natural language. To overcome the disadvantage of manual induction of syntactic rules, this paper proposes a new machine learning approach based on a sequence alignment algorithm. Firstly, the description instances of spatial relations in a large-scale annotated corpus are extracted and analyzed, and the sequence alignment algorithm is used to calculate the pattern similarity between instances of spatial relations. Then, the instances with high similarity are generalized aspopularly used syntactic rules. Finally, these rules are used for extraction spatial relations in a test data to evaluate their validation. The experimental results indicate that the generalized rules can achieve better performance than those rules induced according to occurrence frequency in the corpus.

Keywords

GIS Spatial relation Sequence alignment Syntactic pattern 

Notes

Acknowledgments

This work was supported by National Natural Science Foundation of China (No. 40971231); the Graduates’ scientific research and innovation plan of Jiangsu Province (No. CXZZ12_0394).

References

  1. 1.
    Jun, Chen, Renliang, Zhao: Spatial relations in GIS: a survey on its key issues and research progress. Acta Geodaetica et Cartographica Sinica 28(2), 95–100 (1999)Google Scholar
  2. 2.
    Shihong, Du, Qiming, Qin, Qiao, Wang: The Spatial relations in GIS and their applications. Earth Sci. Front. 13(3), 069–080 (2006)Google Scholar
  3. 3.
    Du, S., Wang, Q., Li, Z.: Definitions of natural language spatial relations in GIS. Geomatics Inf. Sci. Wuhan Univ. 30(6), 533–538 (2005)Google Scholar
  4. 4.
    Mark, M.D., Comas, D., Egenhofer, M.J., et al. Evaluating and refining computational models of spatial relations through cross-linguistic human-subjects testing. In: Frank, A., Kuhn, W. Spatial Information Theory: A theoretical Basis for GIS, International Conference COSIT, Semmering, Austria, Lecture Notes in Computer Science, vol. 988, pp. 553–568. Springer-Verlag, Berlin (1995)Google Scholar
  5. 5.
    Egenhofer, M.J.: Locational SQL: syntax extensions. Surveying Engineering Program, University of Maine (1987)Google Scholar
  6. 6.
    Coyne, B., Sproat, R.: Wordseye: an automatic text-to-scene conversion system. In: Proceedings of the 28th Annual Conference on Computer graphics and Interactive Techniques, pp. 487-496. ACM, Los Angeles 12–17 Aug 2001Google Scholar
  7. 7.
    Reinberger, M.-L.: Automatic extraction of spatial relations. In: Proceedings of the TEMA workshop, EPIA 2005, Portugal (2005)Google Scholar
  8. 8.
    Le, X., Yang C., Yu W.: Spatial concept extraction based on spatial semantic role in natural language. Editorial Board Geomatics Inf. Sci. Wuhan Univ. 30(12), 1100–1103 (2005)Google Scholar
  9. 9.
    Liu, Y., Gao, Y., Lin, B.: Research on GIS path reconstruction based on constrained Chinese language. J. Remote Sens. 8(4), 323–330 (2004)Google Scholar
  10. 10.
    Zhang, X., Lv, G.: Natural-language spatial relations and their applications in GIS.Geo-information science, 9(6), 77–81 (2007)Google Scholar
  11. 11.
    Zhang, C., Zhang X., Jiang W.: Rule-based extraction of spatial relations in natural language Text. In: Proceedings of the 2009 International Conference on Computational Intelligence and software Engineering (2009)Google Scholar
  12. 12.
    Chen, X., Hu Y., Lu R.: Extraction of entity relation templates from text collections. Comput. Eng. 33(22), 199–201; 9(6), 77–81 (2007)Google Scholar
  13. 13.
    Xu Z.: Bioinformatics. Tsinghua Unversity Press, Beijing (2008)Google Scholar

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Key Laboratory of Virtual Geography Environment Ministry of EducationNanjing Normal UniversityNanjingChina

Personalised recommendations