Fuzzy Logic Ranking for Personalized Geographic Information Retrieval

  • Garnett Wilson
  • Rodolphe Devillers
  • Orland Hoeber
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 179)

Abstract

This work describes a novel fuzzy logic system designed to meet the real world demand of providing intelligent ranking to large repositories of documents previously encoded with non-fuzzy (crisp) metadata. The fuzzy logic prototype was tested in practice to complement the GeoConnections Discovery Portal, which is a web portal for specialized search and retrieval of Canadian geographic data resources via an associated web service. Users of the portal are able to query the system and then filter their search results by selecting topic categories, spatial and temporal extents, and resource types. The authors present a fuzzy logic information retrieval system that utilizes document metadata, and compare it to an unranked listing, standard term frequency-inverse document frequency (TF-IDF) ranking, and a TF-IDF/fuzzy hybrid system. Results indicate that the fuzzy logic system provided the overall highest precision among the top ranked documents for searches by an expert user, and that these results were robust with respect to the number of results returned by a number of different query types.

Keywords

Fuzzy Logic User Profile Fuzzy Logic System Logic Hybrid Fuzzy Ontology 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors would like to acknowledge programming assistance provided by Derek Leblanc, the financial assistance of a Canadian GEOIDE Network grant held by the second author, and the assistance of the GeoConnections initiative in accessing their web services.

References

  1. 1.
    Bütcher, S., Clarke, C., Cormack, G.: Information Retrieval: Implementing and Evaluating Search Engines. MIT Press, Cambridge (2010)Google Scholar
  2. 2.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval: The Concepts and Terminology Behind Search. 2nd edn. Addison-Wesley, Harlow (2011)Google Scholar
  3. 3.
    Castellano, G., Dell’Agnello, D., Fanelli, A.M., Mencar, C., Torsello, M.A.: A competitive learning strategy for adapting fuzzy user profiles. In: 10th International Conference on Intelligent Systems Design and Applications, ISDA 2010, pp. 959–964, Nov 29–Dec 1 (2010)Google Scholar
  4. 4.
    Han, E.-H., Karypis, G.: Centroid-based document classification: analysis and experimental results. In: Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery, PKDD ’00, pp. 424–431, Springer-Verlag, London (2000)Google Scholar
  5. 5.
    Holi, M., Hyvönen, E., Lindgren, P.: Integrating tf-idf weighting with fuzzy view-based search. In: Proceedings of the ECAI Workshop on Text-Based, Information Retrieval (TIR-06) (2006)Google Scholar
  6. 6.
    Jones, C.B., Purves, R.S.: Geographical information retrieval. Int. J. Geogr. Inf. Sci. 22(3), 219–228 (2008)CrossRefGoogle Scholar
  7. 7.
    Leite, M.A.A., Ricarte, I.L.: Document retrieval using fuzzy related geographic ontologies. In: Proceeding of the 2nd International Workshop on Geographic Information Retrieval, GIR ’08, pp. 47–54, ACM, New York (2008)Google Scholar
  8. 8.
    Mencar, C., Torsello, M., Dell’Agnello, D., Castellano, G., Castiello, C.: Modeling user preferences through adaptive fuzzy profiles. In: 9th International Conference on Intelligent Systems Design and Applications, ISDA 2009, pp. 1031–1036, Nov 30–Dec 2 (2009)Google Scholar
  9. 9.
    Micarelli, A., Gasparetti, F., Sciarrone, F., Gauch, S.: Personalized search on the world wide web. In: Brusilovsky, P., Kobsa, A., Nejdl, W. (eds.) The Adaptive Web: Methods and Strategies of Web Personalization, pp. 195–230. Springer-Verlag, Berlin (2007)Google Scholar
  10. 10.
    Porter, M.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)CrossRefGoogle Scholar
  11. 11.
    Ross, T.: Fuzzy Logic with Engineering Applications. Wiley, West Sussex (2004)MATHGoogle Scholar
  12. 12.
    Rubens, N.O.: The application of fuzzy logic to the construction of the ranking function of information retrieval systems. Comput. Model. New Technol. 10(1), 20–27 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Garnett Wilson
    • 1
  • Rodolphe Devillers
    • 2
  • Orland Hoeber
    • 1
  1. 1.Department of Computer ScienceMemorial University of NewfoundlandSt. John’sCanada
  2. 2.Department of GeographyMemorial University of NewfoundlandSt. John’sCanada

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