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The applied AI and natural language processing workshop : explore practical ways to transform your simple projects into powerful intelligent applications
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BLLDB
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UB Frankfurt Linguistik
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CAS: corpus of clinical cases in French
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In: ISSN: 2041-1480 ; Journal of Biomedical Semantics ; https://hal.archives-ouvertes.fr/hal-03021064 ; Journal of Biomedical Semantics, BioMed Central, 2020, ⟨10.1186/s13326-020-00225-x⟩ (2020)
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Application-Oriented Approach for Detecting Cyberaggression in Social Media
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In: International Conference on Applied Human Factors and Ergonomics ; https://hal.archives-ouvertes.fr/hal-02903422 ; International Conference on Applied Human Factors and Ergonomics, Jul 2020, San Diego, United States. pp.129-136, ⟨10.1007/978-3-030-51328-3_19⟩ ; https://link.springer.com/chapter/10.1007%2F978-3-030-51328-3_19 (2020)
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Capitalizing on a TREC Track to Build a Tweet Summarization Dataset
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In: CIRCLE 2020 ; Proceedings of the Joint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020) ; Joint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020) ; https://hal.archives-ouvertes.fr/hal-03095613 ; Joint Conference of the Information Retrieval Communities in Europe (CIRCLE 2020), Université de Toulouse, France, Jul 2020, Samatan, Gers, France. pp.1-9 ; http://ceur-ws.org/Vol-2621/CIRCLE20_20.pdf (2020)
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The Impact of Specialized Corpora for Word Embeddings in Natural Langage Understanding.
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In: ISSN: 0926-9630 ; EISSN: 1879-8365 ; Studies in Health Technology and Informatics ; https://hal.inria.fr/hal-03476839 ; Studies in Health Technology and Informatics, IOS Press, 2020, 270, pp.432-436. ⟨10.3233/SHTI200197⟩ (2020)
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BASE
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A study of semantic projection from single word terms to multi-word terms in the environment domain
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In: 6th International Workshop on Computational Terminology (COMPUTERM 2020) ; https://hal.archives-ouvertes.fr/hal-03478024 ; 6th International Workshop on Computational Terminology (COMPUTERM 2020), May 2020, Marseille, France. pp.ISBN 979-10-95546-57-3 (2020)
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Lexical content as a cooperation aide: a study based on Java software
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BASE
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Représentations lexicales pour la détection non supervisée d'événements dans un flux de tweets : étude sur des corpus français et anglais
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In: Extraction et Gestion des connaissances, EGC 2020 ; https://hal-centralesupelec.archives-ouvertes.fr/hal-02432990 ; Extraction et Gestion des connaissances, EGC 2020, Jan 2020, Bruxelles, Belgique (2020)
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Patch-based Identification of Lexical Semantic Relations
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In: 42nd European Conference on Information Retrieval (ECIR) ; https://hal.archives-ouvertes.fr/hal-02400661 ; 42nd European Conference on Information Retrieval (ECIR), 2020, Lisbon, Portugal (2020)
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Designing an IIR Research Apparatus with Users with Severe Intellectual Disability
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In: ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR) ; https://hal-amu.archives-ouvertes.fr/hal-02470797 ; ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR), Mar 2020, Vancouver, Canada. pp.412-416, ⟨10.1145/3343413.3378008⟩ (2020)
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Design, development and validation of a system for automatic help to medical text understanding
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In: Alfano, Marco orcid:0000-0001-7200-9547 , Lenzitti, Biagio orcid:0000-0003-2664-7788 , Lo Bosco, Giosuè orcid:0000-0002-1602-0693 , Muriana, Cinzia orcid:0000-0002-9951-1761 , Piazza, Tommaso orcid:0000-0001-5881-1410 and Vizzini, Giovanni orcid:0000-0002-3273-1719 (2020) Design, development and validation of a system for automatic help to medical text understanding. International Journal of Medical Informatics, 138 . ISSN 1386-5056 (2020)
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Bilingual lexicon induction across orthographically-distinct under-resourced Dravidian languages
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In: Chakravarthi, Bharathi Raja orcid:0000-0002-4575-7934 , Rajasekaran, Navaneethan, Arcan, Mihael orcid:0000-0002-3116-621X , McGuinness, Kevin orcid:0000-0003-1336-6477 , O'Connor, Noel E. orcid:0000-0002-4033-9135 and McCrae, John P. orcid:0000-0002-7227-1331 (2020) Bilingual lexicon induction across orthographically-distinct under-resourced Dravidian languages. In: 7th Workshop on NLP for Similar Languages, Varieties and Dialects, 13 Dec 2020, Barcelona, Spain (Online). (2020)
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Machine translation of user-generated content
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Lohar, Pintu. - : Dublin City University. School of Computing, 2020. : Dublin City University. ADAPT, 2020
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In: Lohar, Pintu (2020) Machine translation of user-generated content. PhD thesis, Dublin City University. (2020)
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Investigating query expansion and coreference resolution in question answering on BERT
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In: Bhattacharjee, Santanu, Haque, Rejwanul orcid:0000-0003-1680-0099 , Maillette de Buy Wenniger, Gideon and Way, Andy orcid:0000-0001-5736-5930 (2020) Investigating query expansion and coreference resolution in question answering on BERT. In: 25th International Conference on Natural Language & Information Systems (NLDB 2020)), 24 - 26 June 2020, Saarbrücken, Germany (Online). ISBN 978-3-030-51309-2 (2020)
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Abstract:
The Bidirectional Encoder Representations from Transformers (BERT) model produces state-of-the-art results in many question answering (QA) datasets, including the Stanford Question Answering Dataset (SQuAD). This paper presents a query expansion (QE) method that identifies good terms from input questions, extracts synonyms for the good terms using a widely-used language resource, WordNet, and selects the most relevant synonyms from the list of extracted synonyms. The paper also introduces a novel QE method that produces many alternative sequences for a given input question using same-language machine translation (MT). Furthermore, we use a coreference resolution (CR) technique to identify anaphors or cataphors in paragraphs and substitute them with the original referents. We found that the QA system with this simple CR technique significantly outperforms the BERT baseline in a QA task. We also found that our best-performing QA system is the one that applies these three preprocessing methods (two QE and CR methods) together to BERT, which produces an excellent F 1 score (89.8 F1 points) in a QA task. Further, we present a comparative analysis on the performances of the BERT QA models taking a variety of criteria into account, and demonstrate our findings in the answer span prediction task.
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Keyword:
Computational linguistics; Computer engineering; coreference resolution; Information retrieval; Machine learning; Machine translating; machine translation; neural machine translation; query expansion; question answering
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URL: http://doras.dcu.ie/24561/
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Using Sentiment Analysis for Pseudo-Relevance Feedback in Social Book Search
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In: ICTIR '20: The 2020 ACM SIGIR International Conference on the Theory of Information Retrieval ; https://hal.archives-ouvertes.fr/hal-03124566 ; ICTIR '20: The 2020 ACM SIGIR International Conference on the Theory of Information Retrieval, Sep 2020, Stavanger, Norway. pp.29-32, ⟨10.1145/3409256.3409847⟩ ; https://ictir2020.org (2020)
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A Hybrid Bi-LSTM-CRF Model for Sequence Labeling Applied to the Sourcing Domain
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In: PFIA-APIA 2020 - 5ème Conférence Nationale sur les Applications Pratiques de l’Intelligence Artificielle ; https://hal.inria.fr/hal-02932095 ; PFIA-APIA 2020 - 5ème Conférence Nationale sur les Applications Pratiques de l’Intelligence Artificielle, Jun 2020, Angers, France (2020)
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Dataset for Temporal Analysis of English-French Cognates
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In: Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020) ; 12th Conference on Language Resources and Evaluation (LREC 2020) ; https://hal.archives-ouvertes.fr/hal-03026957 ; 12th Conference on Language Resources and Evaluation (LREC 2020), May 2020, Marseille, France. pp.855-859, ⟨10.5281/zenodo.3693650⟩ (2020)
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