Abstract
Named entity recognition aims at locating elements in a given text and classifying them according to pre-defined categories, such as the names of persons, organisations, locations, quantities, etc. This paper proposes an approach to recognise the location names by extracting them from unstructured Italian language texts. We put forward the use of the framework MapReduce for this task, since it is more robust than a classical analysis when data are unknown and assists at parallelising processing, which is essential for a large amount of data.
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Acknowledgements
This work has been partially supported by project PRIME “Piattaforma di Reasoning Integrata, Multimedia, Esperta” funded by Regione Sicilia within PO FESR Sicilia 2007/2013 framework, and FIR project “Organizzazione e trattamento di trascrizioni e testi in scenari di security”, code 375E90.
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Napoli, C., Tramontana, E., Verga, G. (2016). Extracting Location Names from Unstructured Italian Texts Using Grammar Rules and MapReduce. In: Dregvaite, G., Damasevicius, R. (eds) Information and Software Technologies. ICIST 2016. Communications in Computer and Information Science, vol 639. Springer, Cham. https://doi.org/10.1007/978-3-319-46254-7_48
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DOI: https://doi.org/10.1007/978-3-319-46254-7_48
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