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Conference papers

Facetted Search on Extracted Fusion Tables Data for Digital Cities

Abstract : Digital cities of the future should provide digital information about points-of-interest (POIs) for virtually any user context. Starting from several Google Fusion tables about city POIs, we extracted and transferred useful POI data to RDF to be accessible by SPARQL requests. In this initial application context, we concentrated on museum and restaurant resources as the result of a precision-oriented information extraction part. With the current application system we are able to retrieve, filter, and order digital cities POI data in multiple ways. With the help of facets, a user can browse the museums and restaurants; he or she can also filter the relevant objects according to available metadata criteria such as city, country, and POI categories. Different views allow us to visualize the objects of interest as tables, thumbnails, or POIs on an interactive map. In addition, if complementary information from DBpedia about museum and restaurant records from the cities they are located in is available, the information can be retrieved and displayed at query time.
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Contributor : Chantal Reynaud Connect in order to contact the contributor
Submitted on : Tuesday, February 12, 2013 - 11:22:13 AM
Last modification on : Sunday, June 26, 2022 - 11:58:16 AM


  • HAL Id : hal-00787478, version 1



Jochen Setz, Gianluca Quercini, Daniel Sonntag, Chantal Reynaud. Facetted Search on Extracted Fusion Tables Data for Digital Cities. Poster and Demo track of the 35th German Conference on Artificial Intelligence (KI-2012), Sep 2012, Saarbrücken, Germany. ⟨hal-00787478⟩



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