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.
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Notes
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It is not possible to know the number, or content, of all documents in all repositories served by the web portal.
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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.
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Wilson, G., Devillers, R., Hoeber, O. (2013). Fuzzy Logic Ranking for Personalized Geographic Information Retrieval. In: Kudělka, M., Pokorný, J., Snášel, V., Abraham, A. (eds) Proceedings of the Third International Conference on Intelligent Human Computer Interaction (IHCI 2011), Prague, Czech Republic, August, 2011. Advances in Intelligent Systems and Computing, vol 179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31603-6_10
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