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An Introduction to Complex Systems: Making Sense of a Changing World
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In: Faculty Books (2019)
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Should we use movie subtitles to study linguistic patterns of conversational speech? A study based on French, English and Taiwan Mandarin
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In: Third International Symposium on Linguitic Patters of Spontaneous Speech ; https://hal.archives-ouvertes.fr/hal-02385689 ; Third International Symposium on Linguitic Patters of Spontaneous Speech, Nov 2019, Taipei, Taiwan ; http://lpss2019.ling.sinica.edu.tw/ (2019)
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Segmentability Differences Between Child-Directed and Adult-Directed Speech: A Systematic Test With an Ecologically Valid Corpus
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In: EISSN: 2470-2986 ; Open Mind ; https://hal.archives-ouvertes.fr/hal-02274050 ; Open Mind, MIT Press, 2019, 3, pp.13-22. ⟨10.1162/opmi_a_00022⟩ (2019)
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A computational account of virtual travelers in the Montagovian generative lexicon
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In: The Semantics of Dynamic Space in French ; https://hal.archives-ouvertes.fr/hal-02093536 ; Michel Aurnague; Dejan Stosic. The Semantics of Dynamic Space in French, John Benjamins, pp.407-450, 2019, Part IV. Formal and computational aspects of motion-based narrations, 9789027203205. ⟨10.1075/hcp.66.09lef⟩ ; https://benjamins.com/catalog/hcp.66.09lef (2019)
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Towards TreeLex++: Syntactico-Semantic Lexical Resource for French
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In: Language & Technology Conference ; https://hal.archives-ouvertes.fr/hal-02120183 ; Language & Technology Conference, May 2019, Poznan, Poland (2019)
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Cross-lingual parsing with polyglot training and multi-treebank learning: a Faroese case study
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In: Barry, James orcid:0000-0003-3051-585X , Wagner, Joachim orcid:0000-0002-8290-3849 and Foster, Jennifer orcid:0000-0002-7789-4853 (2019) Cross-lingual parsing with polyglot training and multi-treebank learning: a Faroese case study. In: The 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019), 3 - 5 Nov 2019, Hong Kong, China. ISBN 978-1-950737-78-9 (2019)
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Selecting artificially-generated sentences for fine-tuning neural machine translation
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In: Poncelas, Alberto orcid:0000-0002-5089-1687 and Way, Andy orcid:0000-0001-5736-5930 (2019) Selecting artificially-generated sentences for fine-tuning neural machine translation. In: 12th International Conference on Natural Language Generation, 29 Oct - 1 Nov 2019, Tokyo, Japan. (2019)
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Automatic error classification with multiple error labels
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In: Popović, Maja orcid:0000-0001-8234-8745 and Vilar, David (2019) Automatic error classification with multiple error labels. In: MT Summit XVII, 19 - 23 Aug 2019, Dublin, Ireland. (2019)
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Combining SMT and NMT back-translated data for efficient NMT
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In: Poncelas, Alberto orcid:0000-0002-5089-1687 , Popović, Maja orcid:0000-0001-8234-8745 , Shterionov, Dimitar orcid:0000-0001-6300-797X , Maillette de Buy Wenniger, Gideon and Way, Andy orcid:0000-0001-5736-5930 (2019) Combining SMT and NMT back-translated data for efficient NMT. In: Recent Advances in Natural Language Processing (RANLP 2019), 2-4 Sept 2019, Varna, Bulgaria. (2019)
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Transductive data-selection algorithms for fine-tuning neural machine translation
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In: Poncelas, Alberto orcid:0000-0002-5089-1687 , Maillette de Buy Wenniger, Gideon orcid:0000-0001-8427-7055 and Way, Andy orcid:0000-0001-5736-5930 (2019) Transductive data-selection algorithms for fine-tuning neural machine translation. In: The 8th Workshop on Patent and Scientific Literature Translation, Dublin, Ireland. (2019)
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Investigating backtranslation for the improvement of English-Irish machine translation
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In: Dowling, Meghan orcid:0000-0003-1637-4923 , Lynn, Teresa and Way, Andy orcid:0000-0001-5736-5930 (2019) Investigating backtranslation for the improvement of English-Irish machine translation. Teanga, 26 . pp. 1-25. ISSN 0332-205X (2019)
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Predicting students' academic performance and main behavioral features using data mining techniques
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In: Almutairi, Suad, Shaiba, Hadil and Bezbradica, Marija orcid:0000-0001-9366-5113 (2019) Predicting students' academic performance and main behavioral features using data mining techniques. In: Advances in Data Science, Cyber Security and IT Applications. ICC 2019., 10-12 Dec 2019, Riyadh, Saudi Arabia. ISBN 978-3-030-36364-2 (2019)
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Abstract:
Creating learning environments, where students, parents, and teachers are linked to a learning process, helps study their overall impact on the students’ performance. Data mining can analyze these inter-relationships and thus enable the prediction of academic performance to improve the student’s academic level. The main factors that affect the student’s performance were selected using feature selection methods. An analysis of the crucial features was investigated to better understand the data. One of the main outcomes found is the impact of the behavioral features on the students’ academic performance. Moreover, gender and relation demographical features are another important features found. It was evedent that there is an academic disparity between genders, as females constitute the most outstanding students. Furthermore, mothers have a clear role in student academic excellence. Six machine learning methods were used and tested to predict the studnet’s performance, namely random forest, logistic regression, XGBoost, MLP, and ensemble learning using bagging and voting. Of all the methods, the random forest got the highest accuracy with 10-best selected features that reached 77%. Overfitting was addressed successfully by tuning the hyper-parameters. The results show that data mining can accurately predict the students’ performance level, as well as highlight the most influential features.
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Keyword:
Artificial intelligence; Computational linguistics; Computer simulation; deep learning; Educational data mining; learning analytics; Machine learning
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URL: http://doras.dcu.ie/26154/
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What is the impact of raw MT on Japanese users of Word preliminary results of a usability study using eye-tracking
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In: Guerberof Arenas, Ana orcid:0000-0001-9820-7074 , Moorkens, Joss orcid:0000-0003-4864-5986 and O'Brien, Sharon orcid:0000-0003-4864-5986 (2019) What is the impact of raw MT on Japanese users of Word preliminary results of a usability study using eye-tracking. In: XVII Machine Translation Summit, 19-23 Aug 2019, Dublin, Ireland. (In Press) (2019)
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Learning to Parse Grounded Language using Reservoir Computing
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In: ICDL-Epirob 2019 - Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics ; https://hal.inria.fr/hal-02422157 ; ICDL-Epirob 2019 - Joint IEEE 9th International Conference on Development and Learning and Epigenetic Robotics, Aug 2019, Olso, Norway. ⟨10.1109/devlrn.2019.8850718⟩ ; https://ieeexplore.ieee.org/abstract/document/8850718 (2019)
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Phonetic lessons from automatic phonemic transcription: preliminary reflections on Na (Sino-Tibetan) and Tsuut’ina (Dene) data
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In: ICPhS XIX (19th International Congress of Phonetic Sciences) ; https://halshs.archives-ouvertes.fr/halshs-02059313 ; ICPhS XIX (19th International Congress of Phonetic Sciences), Aug 2019, Melbourne, Australia ; https://icphs2019.org/icphs2019-fullpapers/ (2019)
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Willkommenskultur: A Computational and Socio-linguistic Study of Modern German Discourse on Migrant Populations
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In: Hartnett, Sabina. (2019). Willkommenskultur: A Computational and Socio-linguistic Study of Modern German Discourse on Migrant Populations. Transit, 12(1). Retrieved from: http://www.escholarship.org/uc/item/1x84x67r (2019)
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COMPARING SOLUTIONS TO THE LINKING PROBLEM USING AN INTEGRATED QUANTITATIVE FRAMEWORK OF LANGUAGE ACQUISITION
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In: LANGUAGE, vol 95, iss 4 (2019)
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Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing
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In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02425462 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2019, 45 (3), pp.559-601. ⟨10.1162/coli_a_00357⟩ ; https://www.mitpressjournals.org/doi/abs/10.1162/coli_a_00357 (2019)
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Modelling the Semantic Change Dynamics using Diachronic Word Embedding
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In: 11th International Conference on Agents and Artificial Intelligence (NLPinAI Special Session) ; https://hal.archives-ouvertes.fr/hal-02048377 ; 11th International Conference on Agents and Artificial Intelligence (NLPinAI Special Session), Feb 2019, Prague, Czech Republic (2019)
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