Unsupervised Keyword Extraction From Polish Legal Texts

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dc.contributor.authorJungiewicz, Michał
dc.contributor.authorŁopuszyński, Michał
dc.contributor.organizationInterdisciplinary Centre for Mathematical and Computational Modelling, University of Warsawpl_PL
dc.contributor.organizationFaculty of Electronics and Information Technology, Warsaw University of Technologypl_PL
dc.date.accessioned2015-01-27T10:18:54Z
dc.date.available2015-01-27T10:18:54Z
dc.date.issued2014
dc.description.abstractIn this work, we present an application of the recently pro- posed unsupervised keyword extraction algorithm RAKE to a corpus of Polish legal texts from the field of public procurement. RAKE is essen- tially a language and domain independent method. Its only language- specific input is a stoplist containing a set of non-content words. The performance of the method heavily depends on the choice of such a stoplist, which should be domain adopted. Therefore, we complement RAKE algorithm with an automatic approach to selecting non-content words, which is based on the statistical properties of term distribution.en
dc.description.epersonMichał Łopuszyński
dc.identifier.urihttp://dx.doi.org/10.1007/978-3-319-10888-9_7
dc.identifier.urihttps://depot.ceon.pl/handle/123456789/6094
dc.publisherSpringerpl_PL
dc.relation.ispartofseriesLecture Notes in Computer Science;8686
dc.rightsDozwolony użytek
dc.subjectlegal textsen
dc.subjectunsupervised learningen
dc.subjectkeyword extractionen
dc.titleUnsupervised Keyword Extraction From Polish Legal Textsen
dc.typeconferencePaperpl_PL
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