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Wortbildung in Gesprochener Sprache I : Die Substantiv-, Verb- Und Adjektiv-Zusammensetzungen und -Ableitungen Im Häufigkeitswörterbuch Gesprochender Sprache . Erster Hauptteil - Substantiv
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UB Frankfurt Linguistik
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Genetic and Environmental Influences on the Visual Word Form and Fusiform Face Areas.
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In: ISSN: 1047-3211 ; EISSN: 1460-2199 ; Cerebral Cortex ; https://hal-pasteur.archives-ouvertes.fr/pasteur-01579771 ; Cerebral Cortex, Oxford University Press (OUP), 2015, 25 (9), pp.2478-93. ⟨10.1093/cercor/bhu048⟩ (2015)
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Generating and executing complex natural language queries across linked data
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In: International Congress on Medical Informatics ; https://hal.archives-ouvertes.fr/hal-01971222 ; International Congress on Medical Informatics, Jan 2015, Sao Paulo, Brazil (2015)
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Extracting biomedical events from pairs of text entities
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In: ISSN: 1471-2105 ; BMC Bioinformatics ; https://hal.archives-ouvertes.fr/hal-01313324 ; BMC Bioinformatics, BioMed Central, 2015, 16 (Suppl 10), pp.S8. ⟨10.1186/1471-2105-16-S10-S8⟩ ; http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-16-S10-S8 (2015)
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Abstract:
International audience ; BackgroundHuge amounts of electronic biomedical documents, such as molecular biology reports or genomic papers are generated daily. Nowadays, these documents are mainly available in the form of unstructured free texts, which require heavy processing for their registration into organized databases. This organization is instrumental for information retrieval, enabling to answer the advanced queries of researchers and practitioners in biology, medicine, and related fields. Hence, the massive data flow calls for efficient automatic methods of text-mining that extract high-level information, such as biomedical events, from biomedical text. The usual computational tools of Natural Language Processing cannot be readily applied to extract these biomedical events, due to the peculiarities of the domain. Indeed, biomedical documents contain highly domain-specific jargon and syntax. These documents also describe distinctive dependencies, making text-mining in molecular biology a specific discipline.ResultsWe address biomedical event extraction as the classification of pairs of text entities into the classes corresponding to event types. The candidate pairs of text entities are recursively provided to a multiclass classifier relying on Support Vector Machines. This recursive process extracts events involving other events as arguments. Compared to joint models based on Markov Random Fields, our model simplifies inference and hence requires shorter training and prediction times along with lower memory capacity. Compared to usual pipeline approaches, our model passes over a complex intermediate problem, while making a more extensive usage of sophisticated joint features between text entities. Our method focuses on the core event extraction of the Genia task of BioNLP challenges yielding the best result reported so far on the 2013 edition.
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Keyword:
[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; Information Extraction; Machine Learning; Natural Language Processing
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URL: https://hal.archives-ouvertes.fr/hal-01313324
https://doi.org/10.1186/1471-2105-16-S10-S8
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Semantic Similarity from Natural Language and Ontology Analysis
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In: https://hal.archives-ouvertes.fr/hal-01288380 ; Morgan & Claypool publishers, 8 (1), pp.254, 2015, Synthesis Lectures on Human Language Technologies, Graeme Hirst, 978-1-62705-446-1. ⟨10.2200/S00639ED1V01Y201504HLT027⟩ ; http://www.morganclaypool.com/doi/10.2200/S00639ED1V01Y201504HLT027 (2015)
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Features of an Error Correction Memory to Enhance Technical Texts Authoring in LELIE
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In: ISSN: 2234-0068 ; International Journal of Knowledge Content Development & Technology ; https://hal.archives-ouvertes.fr/hal-01303853 ; International Journal of Knowledge Content Development & Technology, 2015, vol. 5 (n° 2), pp. 75-101. ⟨10.5865/IJKCT.2015.5.2.075⟩ (2015)
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Adding new words into a language model using parameters of known words with similar behavior
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In: Proceedings ICNLSP'2015, International Conference on Natural Language and Speech Processing ; International Conference on Natural Language and Speech Processing ; https://hal.inria.fr/hal-01184194 ; International Conference on Natural Language and Speech Processing, Oct 2015, Alger, Algeria (2015)
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Unsupervised Speaker Identification in TV Broadcast Based on Written Names
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In: ISSN: 1558-7916 ; IEEE Transactions on Audio, Speech and Language Processing ; https://hal.archives-ouvertes.fr/hal-01060827 ; IEEE Transactions on Audio, Speech and Language Processing, Institute of Electrical and Electronics Engineers, 2015, 23 (1), pp.57-68. ⟨10.1109/TASLP.2014.2367822⟩ ; https://dl.acm.org/authorize?N46627 (2015)
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Eye-tracking measurements of language processing: developmental differences in children at high risk for ASD
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