Abstract
We present a prototype system for resolving named entities, mentioned in textual documents, into the corresponding Wikipedia entities. This prototype can aid in document analysis, by using the disambiguated references to provide useful information in context.
This research draws on work from two projects supported by Fundação para a Ciência e Técnologia (FCT), namely the projects with references PTDC/EIA-EIA/109840/2009 (SInteliGIS) and UTA-Est/MAI/0006/2009 (REACTION). The work reported on this paper was also supported through INESC-ID’s multianual funding provided by the FCT (PEst-OE/EEI/LA0021/2013).
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References
Anastácio, I., Calado, P., Martins, B.: Supervised learning for linking named entities to wikipedia pages. In: Proceedings of the Text Analysis Conference (2011)
Rao, D., McNamee, P., Dredze, M.: Entity linking: Finding extracted entities in a knowledge base. In: Poibeau, T., et al. (eds.) Multi-source, Multi-lingual Information Extraction and Summarization. Springer (2011)
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Santos, J., Martins, B., Batista, D.S. (2013). Document Analytics through Entity Resolution. In: Lin, X., Manolopoulos, Y., Srivastava, D., Huang, G. (eds) Web Information Systems Engineering – WISE 2013. WISE 2013. Lecture Notes in Computer Science, vol 8181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41154-0_46
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DOI: https://doi.org/10.1007/978-3-642-41154-0_46
Publisher Name: Springer, Berlin, Heidelberg
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