"2014-01-01+01:00"^^ . "Term candidates for a domain, in a language, can be found by taking a corpus for the domain, and a refer- ence corpus for the language identifying the grammatical shape of a term in the language tokenising, lemmatising and POS-tagging both corpora identifying (and counting) the items in each corpus which match the grammatical shape for each item in the domain corpus, compar- ing its frequency with its frequency in the refence corpus. Then, the items with the highest frequency in the domain corpus in comparison to the reference cor- pus will be the top term candidates. None of the steps above are unusual or innova- tive for NLP (see, e. g., (Aker et al., 2013), (Go- jun et al., 2012)). However it is far from trivial to implement them all, for numerous languages, in an environment that makes it easy for non- programmers to find the terms in a domain. This is what we have done in the Sketch Engine (Kilgarriff et al., 2004), and will demonstrate." . "Finding Terms in Corpora for Many Languages with the Sketch Engine"@en . "5"^^ . "Finding Terms in Corpora for Many Languages with the Sketch Engine"@en . . "Kilgarriff, Adam" . "Gothenburg, Sweden" . . . . . "Gothenburg, Sweden" . "Term candidates for a domain, in a language, can be found by taking a corpus for the domain, and a refer- ence corpus for the language identifying the grammatical shape of a term in the language tokenising, lemmatising and POS-tagging both corpora identifying (and counting) the items in each corpus which match the grammatical shape for each item in the domain corpus, compar- ing its frequency with its frequency in the refence corpus. Then, the items with the highest frequency in the domain corpus in comparison to the reference cor- pus will be the top term candidates. None of the steps above are unusual or innova- tive for NLP (see, e. g., (Aker et al., 2013), (Go- jun et al., 2012)). However it is far from trivial to implement them all, for numerous languages, in an environment that makes it easy for non- programmers to find the terms in a domain. This is what we have done in the Sketch Engine (Kilgarriff et al., 2004), and will demonstrate."@en . "Rychl\u00FD, Pavel" . . "http://aclweb.org/anthology/E/E14/E14-2014.pdf" . . . "14330" . . . . "Jakub\u00ED\u010Dek, Milo\u0161" . . "terminology; terms; corpora; sketch engine"@en . "4"^^ . "Proceedings of the Demonstrations at the 14th Conferencethe European Chapter of the Association for Computational Linguistics" . . "RIV/00216224:14330/14:00075387!RIV15-MSM-14330___" . "16860" . "Suchomel, V\u00EDt" . . "RIV/00216224:14330/14:00075387" . "The Association for Computational Linguistics" . . "P(LM2010013), S" . . "4"^^ . . "Kov\u00E1\u0159, Vojt\u011Bch" . . . "9781937284756" . . "Finding Terms in Corpora for Many Languages with the Sketch Engine" . . "[7749E15EF4C1]" . "Finding Terms in Corpora for Many Languages with the Sketch Engine" .