Abstract
CroSer (Cross-language Semantic Retrieval) is an ir system able to discover links between e-gov services described in different languages. CroSeR supports public administrators to link their own source catalogs of e-gov services described in any language to a target catalog whose services are described in English and are available in the Linked Open Data (lod) cloud. Our system is based on a cross-language semantic matching method that i) translates service labels in English using a machine translation tool, ii) extracts a Wikipedia-based semantic representation from the translated service labels using Explicit Semantic Analysis (esa), iii) evaluates the similarity between two services using their Wikipedia-based representations. The user selects a service in a source catalog and exploits the ranked list of matches suggested by CroSeR to establish a relation (of type narrower, equivalent, or broader match) with other services in the English catalog. The method is independent from the language adopted in the source catalog and it does not assume the availability of information about the services other than very short text descriptions used as service labels. CroSeR is a web application accessible via http://siti-rack.siti.disco.unimib.it:8080/croser/ .
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Narducci, F., Palmonari, M., Semeraro, G. (2014). CroSeR: Cross-language Semantic Retrieval of Open Government Data. In: de Rijke, M., et al. Advances in Information Retrieval. ECIR 2014. Lecture Notes in Computer Science, vol 8416. Springer, Cham. https://doi.org/10.1007/978-3-319-06028-6_98
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DOI: https://doi.org/10.1007/978-3-319-06028-6_98
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