Abstract
Geographic Information Retrieval is an active and growing research area that focuses on the retrieval of textual documents according to a geographic criteria of relevance. In this work, we propose a reranking function for these systems that combines the retrieval status value calculated by the information retrieval engine and the geographical similarity between the document and the query. The obtained results show that the proposed ranking function always outperforms text-based baseline approaches.
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References
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Perea-Ortega, J.M., García-Cumbreras, M.A., Ureña-López, L.A., García-Vega, M. (2011). Geo-Textual Relevance Ranking to Improve a Text-Based Retrieval for Geographic Queries. In: Muñoz, R., Montoyo, A., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2011. Lecture Notes in Computer Science, vol 6716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22327-3_38
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DOI: https://doi.org/10.1007/978-3-642-22327-3_38
Publisher Name: Springer, Berlin, Heidelberg
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