Trefwoorden:
Publicaties van Ananiadou, S. gesorteerd op eerste auteur
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| , , en , Three BioNLP Tools Powered by the BioLexicon, in: Proceeedings of EACL 2009 Demonstration Session, pagina's 61--64, 2009 |
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| , , en , Biological Event Recognition with Textual Induction, in: Proceedings of 3rd International Symposium on Languages in Biology and Medicine (LBM-2009), pagina's 91--96, 2009 |
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| , , en , How to make the most of NE dictionaries in statistical NER (2008), in: BMC Bioinformatics, 9:Suppl 11(S5) |
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| , , en , How to Make the Most of NE Dictionaries in Statistical NER, in: Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing (BioNLP 2008), pagina's 63--70, Association for Computational Linguistics, 2008 |
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| , en , Extracting Secondary Bio-Event Arguments with Extraction Constraints (2011), in: Computational Intelligence, 27:4(702-721) |
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| , , , , , en , Distributed Document and Phrase Co-embeddings for Descriptive Clustering, in: Proceedings of EACL, pagina's 991-1001, 2017 |
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| , , , , , , , , en , Connecting Text Mining and Pathways using the PathText Resource, in: Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC 2008), pagina's 1736-1740, European Language Resources Association (ELRA), 2008 |
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| , , , , , , , , en , PathText: Text Mining Tools Integrated with Biological Pathway, in: Genomes to Systems Conference 2008 Handbook, pagina's 65, The Consortium for Post-Genome Science, 2008 |
| en , RELATE: Generating a linguistically inspired Knowledge Graph for fine-grained emotion classification, in: Proceedings of LREC 2022, pagina's 6317-6327, 2022 |
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| , , en , A Narrative Literature Review of Natural Language Processing Applied to the Occupational Exposome (2022), in: Int. J. Environ. Res. Public Health, 19:14(8544) |
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| , , , en , Classifying suicide-related content and emotions on Twitter using Graph Convolutional Neural Networks (2022), in: IEEE Transactions on Affective Computing(1-12) |
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| , , , , en , Identification of Research Hypotheses and New Knowledge from Scientific Literature (2018), in: BMC Medical Informatics and Decision Making, 18(46) |
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| , , , , , en , A Text Mining Pipeline Using Active and Deep Learning for Curating Information in Computational Neuroscience (2018), in: Neuroinformatics |
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| , , , , , , en , A New Corpus to Support Text Mining for the Curation of Metabolites in the ChEBI Database, in: Proceedings of LREC 2018, pagina's 280-285, 2018 |
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| , , , , en , Facilitating and promoting web annotation with Argo, in: Proceedings of I Annotate 2016, 2016 |
| , , , en , An ontology-based disambiguation of terms, in: Proceedings of the Workshop on Mining the Pharmacogenomics Literature, Pacific Symopsium on Biocomputing, 2011 |
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| , en , Thalia: Semantic search engine for biomedical abstracts (2018), in: Bioinformatics, 35:10(1799–1801) |
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| , , en , LitPathExplorer: A Confidence-based Visual Text Analytics Tool for Exploring Literature-Enriched Pathway Models (2017), in: Bioinformatics, 34:8(1389-1397) |
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| , , , , , , , , , en , Are all flavonoids safe for use in Cosmetics?, in: Proceedings of the 30th IFSCC Congress, pagina's Poster S2-296, 2018 |
| , , , , , , , , , , , , en , Role of in silico tools and text mining in the risk assessment of selected alkaloids (2018), in: Toxicology Letters, 295:Supplement 1(S159) |
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| en , A flexible measure of contextual similarity for biomedical terms., in: Proceedings of the Pacific Symposium on Biocomputing 10, pagina's 197--208, 2005 |
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| en , Using automatically learnt verb selectional preferences for classification of biomedical terms (2004), in: Journal of Biomedical Informatics, 37:6(483--497) |
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| , , en , Text mining and ontologies in biomedicine: making sense of raw text. (2005), in: Briefings in Bioinformatics, 6:3(239--251) |
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| , en , MaSTerClass: a case-based reasoning system for the classification of biomedical terms (2005), in: Bioinformatics, 21:11(2748--2758) |
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| , en , Learning to Classify Biomedical Terms through Literature Mining and Genetic Algorithms, in: Intelligent Data Engineering and Automated Learning – IDEAL 2004, pagina's 345--351, Springer-Verlag, 2004 |
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