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1
Mixing Bayesian and Artificial Intelligence approaches for Autonomous Driving
In: Tech M&A 2019 - Minalogic Technical Conference ; https://hal.inria.fr/hal-02434275 ; Tech M&A 2019 - Minalogic Technical Conference, May 2019, Grenoble, France (2019)
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2
A journey in the history of Automated Driving
In: IROS 2019 - IEEE/RSJ International Conference on Intelligent Robots and Systems ; https://hal.inria.fr/hal-02428196 ; IROS 2019 - IEEE/RSJ International Conference on Intelligent Robots and Systems, Nov 2019, Macau, China. pp.1-27 (2019)
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3
Semantic coding in the occipital cortex of early blind individuals
In: https://hal.archives-ouvertes.fr/hal-02018272 ; 2019 (2019)
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4
A Franco-Irish project for the automatic identification of criterial features in learners of English
In: EUROCALL 2019 ; https://hal.univ-rennes2.fr/hal-02496627 ; EUROCALL 2019, Université de Louvain la Neuve, Aug 2019, Louvain la Neuve, Belgium (2019)
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5
How OCR Performance can Impact on the Automatic Extraction of Dictionary Content Structures
In: 19th annual Conference and Members’ Meeting of the Text Encoding Initiative Consortium (TEI) -What is text, really? TEI and beyond ; https://hal.archives-ouvertes.fr/hal-02263276 ; 19th annual Conference and Members’ Meeting of the Text Encoding Initiative Consortium (TEI) -What is text, really? TEI and beyond, Sep 2019, Graz, Austria (2019)
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6
Prototype de feedback visuel des productions écrites d'apprenants francophones de l'anglais sous Moodle
In: Environnements Informatiques pour l'Apprentissage Humain (EIAH'19) ; https://hal.univ-rennes2.fr/hal-02496651 ; Environnements Informatiques pour l'Apprentissage Humain (EIAH'19), University of Paris Sorbonne, Jun 2019, Paris, France (2019)
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7
Prediction of Missing Semantic Relations in Lexical-Semantic Network using Random Forest Classifier
In: CJC PRAXILING 2019 ; https://hal.archives-ouvertes.fr/hal-02356649 ; CJC PRAXILING 2019, Nov 2019, Montpellier, France (2019)
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8
Semantic Flexibility and Grounded Language Learning
In: Proceedings AISB 2019 ; 2019 AISB Convention : Workshop on Language Learning for Artificial Agents ; https://hal.archives-ouvertes.fr/hal-02268932 ; 2019 AISB Convention : Workshop on Language Learning for Artificial Agents, Apr 2019, Falmouth, United Kingdom (2019)
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9
Régularisation spatiale de représentations distribuées de mots
In: Actes de CORIA 2019 ; 16e Conférence francophone en Recherche d'Information et Applications (CORIA 2019) ; https://hal.archives-ouvertes.fr/hal-02494102 ; 16e Conférence francophone en Recherche d'Information et Applications (CORIA 2019), Apr 2019, Lyon, France. pp.1-17 (2019)
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10
Answers Unite! Unsupervised Metrics for Reinforced Summarization Models
In: 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) ; https://hal.sorbonne-universite.fr/hal-02350999 ; 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), Nov 2019, Hong Kong, China. pp.3237-3247, ⟨10.18653/v1/D19-1320⟩ (2019)
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11
LMF Reloaded
In: AsiaLex 2019: Past, Present and Future ; https://hal.inria.fr/hal-02118319 ; AsiaLex 2019: Past, Present and Future, Jun 2019, Istanbul, Turkey (2019)
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12
Apprentissage et évaluation de plongements lexicaux sur un corpus SNCF en langue spécialisée
In: Extraction et Gestion des Connaissances ; https://hal.archives-ouvertes.fr/hal-01982661 ; Extraction et Gestion des Connaissances, Jan 2019, Metz, France (2019)
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13
Logométrie et deep learning. Essai de généalogie politique des discours électoraux aux législatives de 2017
In: Histoire, langues et lexicométrie ; https://hal.archives-ouvertes.fr/hal-02067968 ; Histoire, langues et lexicométrie, Jan 2019, Paris, France (2019)
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14
Investigating the scope of textual metrics for learner level discrimination and learner analytics
In: Learner Corpus Research Conference ; https://hal.archives-ouvertes.fr/hal-02496571 ; Learner Corpus Research Conference, University of Warsaw, Poland, Sep 2019, Varsaw, Poland ; Learner Corpus Association (2019)
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15
Complex networks based word embeddings ; Apprentissage de plongements lexicaux par une approcheréseaux complexes
In: TALN 2019 ; https://hal.archives-ouvertes.fr/hal-02408156 ; TALN 2019, Jul 2019, Toulouse, France (2019)
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16
Towards the Prediction of Semantic Complexity Based on Concept Graphs ; Vers la prédiction de complexité sémantique fondée sur les graphes de concepts
In: 12th International Conference on Educational Data Mining (EDM 2019) ; https://hal.archives-ouvertes.fr/hal-02315319 ; 12th International Conference on Educational Data Mining (EDM 2019), Jul 2019, Montreal, Canada. pp.188-197 ; educationaldatamining.org/EDM2019/ (2019)
Abstract: International audience ; The evaluation of text complexity is an important topic in education. While this objective has been addressed by approaches using lexical and syntactic analysis for decades, semantic complexity is less common, and the recent research works that tackle this question rely on machine learning algorithms that are hardly explainable and are not specifically designed to measure this variable. To address this issue, we explore in this paper the engineering of novel features to evaluate conceptual complexity. Through the construction of a knowledge graph that captures the concepts present in a text and their generalized forms, we measure different graph-based metrics to express such a complexity. Eventually , early-stage evaluations based on a well-known public corpus of students' productions show that the use of these metrics significantly improves performance compared to a state-of-the-art binary neural network classifier.
Keyword: [INFO.EIAH]Computer Science [cs]/Technology for Human Learning; [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; concept complexity; features engineering; knowledge graph; machine learning; neural network; semantic complexity
URL: https://hal.archives-ouvertes.fr/hal-02315319
https://hal.archives-ouvertes.fr/hal-02315319/file/25_paper_154.pdf
https://hal.archives-ouvertes.fr/hal-02315319/document
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17
Investigating Criterial Features of Learner English and Predicting CEFR Levels in French Learners of English
In: EUROCALL 2019 ; https://hal.univ-rennes2.fr/hal-02496615 ; EUROCALL 2019, University of Louvain La Neuve, Aug 2019, Louvain la Neuve, Belgium (2019)
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18
A Supervised Learning Model for the Automatic Assessment of Language Levels Based on Learner Errors
In: EC-TEL 2019 ; https://hal.univ-rennes2.fr/hal-02496688 ; EC-TEL 2019, EATEL, Sep 2019, Delft, Netherlands. pp.308-320 ; http://www.ec-tel.eu/index.php?id=957 (2019)
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19
FEEL: a French Expanded Emotion Lexicon
In: https://hal-lirmm.ccsd.cnrs.fr/lirmm-02136090 ; 2019, ⟨swh:1:dir:35a446bb6f0808aa0db6f5bcd032f43e9ec71591;origin=https://hal.archives-ouvertes.fr/lirmm-02136090;visit=swh:1:snp:9d258bfd8a07f79cb8063b6ac33d6e710bd3e3f3;anchor=swh:1:rev:2266d773cf993b8718a1d7ca1d1bce145118f527;path=/⟩ (2019)
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20
Annotation and data-driven synthesis of facial expressions of French sign language ; Annotation et synthèse basée données des expressions faciales de la Langue des Signes Française
Reverdy, Clement. - : HAL CCSD, 2019
In: https://hal.archives-ouvertes.fr/tel-03080311 ; Computer science. Université Bretagne-Sud, 2019. English (2019)
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