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Greenwashing ou écoblanchiment ? ... : Analyse lexicographique et terminologique d’une tendance de marché ...
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IMIA LaMB WG publications: 'Biomedical Semantics in the Big Data Era' - conference paper introducing the related workshop, MEDINFO, 2015 ...
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IMIA LaMB WG publications: 'Biomedical Semantics in the Big Data Era' - conference paper introducing the related workshop, MEDINFO, 2015 ...
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A deep learning approach to bilingual lexicon induction in the biomedical domain. ...
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Automation on Parnassus: CLIO - A Databank Oriented System for Historians [1980]
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In: Historical Social Research, Supplement ; 29 ; 113-137 (2018)
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A deep learning approach to bilingual lexicon induction in the biomedical domain.
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Comparing and Combining Portuguese Lexical-Semantic Knowledge Bases
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: Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2017. : OASIcs - OpenAccess Series in Informatics. 6th Symposium on Languages, Applications and Technologies (SLATE 2017), 2017
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Building Semantic Trees from XML Documents
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In: ISSN: 1570-8268 ; Journal of Web Semantics ; https://hal-univ-pau.archives-ouvertes.fr/hal-02079156 ; Journal of Web Semantics, Elsevier, 2016, 37-38, pp.1-24. ⟨10.1016/J.WEBSEM.2016.03.002⟩ (2016)
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Abstract:
International audience ; The distributed nature of the Web, as a decentralized system exchanging information between heterogeneous sources, has underlined the need to manage interoperability, i.e., the ability to automatically interpret information in Web documents exchanged between different sources, necessary for efficient information management and search applications. In this context, XML was introduced as a data representation standard that simplifies the tasks of interoperation and integration among heterogeneous data sources, allowing to represent data in (semi-) structured documents consisting of hierarchically nested elements and atomic attributes. However, while XML was shown most effective in exchanging data, i.e., in syntactic interoperability, it has been proven limited when it comes to handling semantics, i.e., semantic interoperability, since it only specifies the syntactic and structural properties of the data without any further semantic meaning. As a result, XML semantic-aware processing has become a motivating challenge in Web data management, requiring dedicated semantic analysis and disambiguation methods to assign well-defined meaning to XML elements and attributes. In this context, most existing approaches: (i) ignore the problem of identifying ambiguous XML elements/nodes, (ii) only partially consider their structural relationships/context, (iii) use syntactic information in processing XML data regardless of the semantics involved, and (iv) are static in adopting fixed disambiguation constraints thus limiting user involvement. In this paper, we provide a new XML Semantic Disambiguation Framework titled XSDFdesigned to address each of the above limitations, taking as input: an XML document, and then producing as output a semantically augmented XML tree made of unambiguous semantic concepts extracted from a reference machine-readable semantic network. XSDF consists of four main modules for: (i) linguistic pre-processing of simple/compound XML node labels and values, (ii) selecting ambiguous XML nodes as targets for disambiguation, (iii) representing target nodes as special sphere neighborhood vectors including all XML structural relationships within a (user-chosen) range, and (iv) running context vectors through a hybrid disambiguation process, combining two approaches: concept-basedand context-based disambiguation, allowing the user to tune disambiguation parameters following her needs. Conducted experiments demonstrate the effectiveness and efficiency of our approach in comparison with alternative methods. We also discuss some practical applications of our method, ranging over semantic-aware query rewriting, semantic document clustering and classification, Mobile and Web services search and discovery, as well as blog analysis and event detection in social networks and tweets. \textcopyright 2016 Elsevier B.V. All rights reserved.
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Keyword:
[INFO]Computer Science [cs]; Context representation; Knowledge bases; Semantic ambiguity; Semantic similarity; Semantic-aware processing; Semi-structured data; Word sense disambiguation; XML
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URL: https://doi.org/10.1016/J.WEBSEM.2016.03.002 https://hal-univ-pau.archives-ouvertes.fr/hal-02079156/document https://hal-univ-pau.archives-ouvertes.fr/hal-02079156/file/459-798-1-SM.pdf https://hal-univ-pau.archives-ouvertes.fr/hal-02079156
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Detailed Phonetic Labeling of Multi-language Database for Spoken Language Processing Applications
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In: DTIC (2015)
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An Annotation Framework for Dense Event Ordering
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In: DTIC (2014)
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ТЕРМИНОЛОГИЯ, ИСПОЛЬЗУЕМАЯ В НОРМАТИВНЫХ ДОКУМЕНТАХ ПО ОБЩИМ ВОПРОСАМ АНАЛИТИЧЕСКОЙ ХИМИИ И МЕТРОЛОГИИ: РАЗРАБОТКА ИНТЕГРИРОВАННОГО ЭЛЕКТРОННОГО ТЕЗАУРУСА
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Improving DoD Energy Efficiency: Combining MMOWGLI Social-Media Brainstorming with Lexical Link Analysis (LLA) to Strengthen the Defense Acquisition Process
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In: DTIC (2013)
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Automated Extraction and Characterisation of Social Network Data from Unstructured Sources -- An Ontology-Based Approach
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In: DTIC (2013)
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Antipsychotic switching in bipolar disorders: a systematic review.
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Therapeutic hypnosis, psychotherapy, and the digital humanities: the narratives and culturomics of hypnosis, 1800-2008
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Synthesis of Systemic Functional Theory & Dynamical Systems Theory for Socio-Cultural Modeling
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In: DTIC (2012)
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Open-Source Multi-Language Audio Database for Spoken Language Processing Applications
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In: DTIC (2012)
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Advanced Subspace Techniques for Modeling Channel and Session Variability in a Speaker Recognition System
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In: DTIC (2012)
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A Multi-Classifier Based Guideline Sentence
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In: ftp://ftp.ncbi.nlm.nih.gov/pub/pmc/d5/b8/Healthc_Inform_Res_2011_Dec_31_17(4)_224-231.tar.gz (2011)
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Joint Terminology: At the Heart of Doctrine
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In: DTIC (2011)
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