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Subject-specific Models for the Analysis of Pathological FDG PET Data
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In: In: Navab, N and Hornegger, J and Wells, WM and Frangi, AF, (eds.) Proceedings of the 18th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). (pp. pp. 651-658). Springer, Cham: Munich, Germany. (2015) (2015)
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Corrigendum: Levy, Mike and Steel, Caroline (2015) Language learner perspectives on the functionality and use of electronic language dictionaries. ReCALL, 27 2: 177-196. doi:10.1017/S095834401400038X
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Exploiting text and network context for geolocation of social media users
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Language learner perspectives on the functionality and use of electronic language dictionaries
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Hand pose recognition from monocular images by geometrical and texture analysis
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ezDI's Semantics-Enhanced Linguistic, NLP, and ML Approach for Health Informatics
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In: Kno.e.sis Publications (2015)
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Un éditeur de définitions formelles pour les connaissances lexicales de la théorie Sens-Texte
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In: IC - 25èmes Journées francophones d'Ingénierie des Connaissances ; https://hal.inria.fr/hal-00967537 ; IC - 25èmes Journées francophones d'Ingénierie des Connaissances, May 2014, Clermont-Ferrand, France. pp.279-281 (2014)
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A language-independent and fully unsupervised approach to lexicon induction and part-of-speech tagging for closely related languages
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In: Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-01022298 ; Language Resources and Evaluation Conference, European Language Resources Association, May 2014, Reykjavik, Iceland (2014)
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Abstract:
International audience ; In this paper, we describe our generic approach for transferring part-of-speech annotations from a resourced language towards an etymologically closely related non-resourced language, without using any bilingual (i.e., parallel) data. We first induce a translation lexicon from monolingual corpora, based on cognate detection followed by cross-lingual contextual similarity. Second, POS information is transferred from the resourced language along translation pairs to the non-resourced language and used for tagging the corpus. We evaluate our methods on three language families, consisting of five Romance languages, three Germanic languages and five Slavic languages. We obtain tagging accuracies of up to 91.6%.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.7: Natural Language Processing; ACM: J.: Computer Applications/J.5: ARTS AND HUMANITIES/J.5.4: Linguistics
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URL: https://hal.inria.fr/hal-01022298 https://hal.inria.fr/hal-01022298/file/lrec14cll.pdf https://hal.inria.fr/hal-01022298/document
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Semantic Annotations for Workflow Interoperability
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In: ISSN: 0350-5596 ; Informatica ; https://hal.inria.fr/hal-01111453 ; Informatica, Slovene Society Informatika, Ljubljana, 2014, 38 (4), pp.347-366 (2014)
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A quantitative approach to evolution of music and philosophy ...
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Gaussian Tree Constraints Applied to Acoustic Linguistic Functional Data ...
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Replicate immunosequencing as a robust probe of B cell repertoire diversity ...
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Testing for Efficacy in Single-Subject Trials with Intervention Analysis ...
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Computerized analysis of coronary artery disease: Performance evaluation of segmentation and tracking of coronary arteries in CT angiograms
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Models, Inference, and Implementation for Scalable Probabilistic Models of Text
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Extracting structured data from publications in the Art Conservation Domain
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