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Un’Analisi Multidimensionale della Ricerca Italiana nel Campo delle Digital Humanities e della Linguistica Computazionale
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SIMPLE-CLIPS ongoing research: more information with less data by implementing inheritance
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In: http://www.lrec-conf.org/proceedings/lrec2008/pdf/598_paper.pdf (2008)
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A lexicon for biology and bioinformatics: the BOOTStrep experience
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In: http://www.lrec-conf.org/proceedings/lrec2008/pdf/576_paper.pdf (2008)
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A lexicon for biology and bioinformatics: the BOOTStrep experience
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In: http://hnk.ffzg.hr/bibl/lrec2008/pdf/576_paper.pdf (2008)
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IOS Press Converting the PAROLE SIMPLE CLIPS Lexicon into RDF with lemon
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In: http://semantic-web-journal.net/system/files/swj487.pdf
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The making of Ancient Greek WordNet
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In: http://www.lrec-conf.org/proceedings/lrec2014/pdf/1071_Paper.pdf
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three anonymous reviewers
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In: http://semantic-web-journal.net/system/files/swj823_0.pdf
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Using LMF to Shape a Lexicon for the Biomedical Domain
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In: http://www.ilc.cnr.it/langtech2008/papers/LangTech2008_MONACHINI_Paper.pdf
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A bilingual dictionary Mexican Sign Language-Spanish/Spanish-Mexican Sign Language
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In: http://www.lrec-conf.org/proceedings/lrec2010/pdf/27_Paper.pdf
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RESEARCH ARTICLE The BioLexicon: a large-scale terminological resource for biomedical text mining Open Access
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In: ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/04/e4/BMC_Bioinformatics_2011_Oct_12_12_397.tar.gz
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Abstract:
Background: Due to the rapidly expanding body of biomedical literature, biologists require increasingly sophisticated and efficient systems to help them to search for relevant information. Such systems should account for the multiple written variants used to represent biomedical concepts, and allow the user to search for specific pieces of knowledge (or events) involving these concepts, e.g., protein-protein interactions. Such functionality requires access to detailed information about words used in the biomedical literature. Existing databases and ontologies often have a specific focus and are oriented towards human use. Consequently, biological knowledge is dispersed amongst many resources, which often do not attempt to account for the large and frequently changing set of variants that appear in the literature. Additionally, such resources typically do not provide information about how terms relate to each other in texts to describe events. Results: This article provides an overview of the design, construction and evaluation of a large-scale lexical and conceptual resource for the biomedical domain, the BioLexicon. The resource can be exploited by text mining tools at several levels, e.g., part-of-speech tagging, recognition of biomedical entities, and the extraction of events in which they are involved. As such, the BioLexicon must account for real usage of words in biomedical texts. In particular, the BioLexicon gathers together different types of terms from several existing data resources into a
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.287.3058
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RESEARCH ARTICLE The BioLexicon: a large-scale terminological resource for biomedical text mining Open Access
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In: http://www.biomedcentral.com/content/pdf/1471-2105-12-397.pdf
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The Language Library: supporting community effort for collective resource production
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In: http://www.lrec-conf.org/proceedings/lrec2012/pdf/396_Paper.pdf
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Towards the establishment of a linguistic linked data network for Italian
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In: http://www.aclweb.org/anthology/W/W13/W13-5512.pdf
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The Language Library: Many Layers, More Knowledge
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In: http://www.aclweb.org/anthology-new/W/W11/W11-3312.pdf
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