2023

Broisin, J., Declercq, C., Fluckiger, C., Parmentier, Y., Peter, Y., & Secq, Y. (2023). Actes de l’atelier APIMU 2023 @ EIAH : Apprendre la Pensée Informatique de la Maternelle à l’Université (p. 1‑40). https://hal.science/hal-04143495

Cerisara, C. (2023). SlowLLM: large language models on consumer hardware. CNRS. https://hal.science/hal-04014493

Cerisara, C., & Parmentier, Y. (2023). Workshop in recognition of Claire Gardent. CNRS. https://hal.science/hal-04149469

Le Berre, G. (2023). Vers la mitigation des biais en traitement neuronal des langues (Theses No. 2023LORR0074). Université de Lorraine ; Université de Montréal. https://theses.hal.science/tel-04206086

Li, C., Huber, P., Xiao, W., Amblard, M., Braud, C., & Carenini, G. (2023). Discourse Structure Extraction from Pre-Trained and Fine-Tuned Language Models in Dialogues. In European Chapter of the Association for Computational Linguistics (EACL) (p. 2562‑2579). Dubrovnik, Croatia. https://hal.univ-lorraine.fr/hal-04031267

Ngo, D. V., & Parmentier, Y. (2023). Towards Sentence-level Text Readability Assessment for French. In Second Workshop on Text Simplification, Accessibility and Readability (TSAR@RANLP2023). Varna, Bulgaria. https://hal.science/hal-04192063

Parmentier, Y., Pogodalla, S., Bawden, R., Labeau, M., & Eshkol-Taravella, I. (2023). Procédure de diffusion des publications de l’ATALA sur les archives ouvertes (p. 17). ATALA. https://hal.science/hal-04258177

Soto, W., Parmentier, Y., & Gardent, C. (2023). Phylogeny-Inspired Soft Prompts For Data-to-Text Generation in Low-Resource Languages. In Y. Arase, B. Hu, & W. Lu (Éd.), IJCNLP-AACL 2023: The 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics. Bali, Indonesia. https://hal.science/hal-04199557

2022

Becerra, L., Favre, B., Gardent, C., & Parmentier, Y. (2022). LIFT-TAL 2022 Actes des journées jointes des Groupements de Recherche Linguistique Informatique, Formelle et de Terrain (LIFT) et Traitement Automatique des Langues (TAL). https://hal.science/hal-03859310

Ben Khelil, C., Ben Othmane Zribi, C., Duchier, D., & Parmentier, Y. (2022). Generating Arabic TAG for syntax-semantics analysis. Natural Language Engineering. https://doi.org/10.1017/S1351324922000109

Benjelloun, I., Koudou, E. A., & Lamiroy, B. (2022). Convolutional network fabric pruning with label noise. https://hal.science/hal-03569057

Chaoub, A., Cerisara, C., Voisin, A., & Iung, B. (2022). Towards interpreting deep learning models for industry 4.0 with gated mixture of experts. In 30th European Signal Processing Conference, EUSIPCO 2022. Belgrade, Serbia. https://hal.science/hal-03785546

Cripwell, L., Legrand, J., & Gardent, C. (2022). Controllable Sentence Simplification via Operation Classification. In Findings of the Association for Computational Linguistics: NAACL 2022 (p. 2091‑2103). Seattle, United States: Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.findings-naacl.161

Fan, A., & Gardent, C. (2022). Generating Full Length Wikipedia Biographies The Impact of Gender Bias on the Retrieval-Based Generation of Women Biographies. In 60th Annual Meeting of the Association for Computational Linguistics (p. 8561‑8576). Dublin, Ireland: Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.acl-long.586

Gontier, F., Serizel, R., & Cerisara, C. (2022). SPICE+: EVALUATION OF AUTOMATIC AUDIO CAPTIONING SYSTEMS WITH PRE-TRAINED LANGUAGE MODELS. https://inria.hal.science/hal-03933981

Han, K., Ferreira, T. C., & Gardent, C. (2022). Generating Questions from Wikidata Triples. In 13th Edition of its Language Resources and Evaluation Conference. Marseille, France. https://hal.science/hal-03909961

Hardouin, C., & Lamirel, J.-C. (2022). Neural Networks for Spatial Models. In Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization (Vol. 533, p. 21‑30). Springer International Publishing. https://doi.org/10.1007/978-3-031-15444-7\_3

Le Berre, G., Cerisara, C., Langlais, P., & Lapalme, G. (2022). Unsupervised multiple-choice question generation for out-of-domain Q&A fine-tuning. In 60th Annual Meeting of the Association for Computational Linguistics (Vol. 2, p. 732‑738). Dublin, Ireland: Association for Computational Linguistics. https://doi.org/10.18653/v1/2022.acl-short.83

Liednikova, A. (2022). Human-Machine Dialogue in the Medical Field. Using Dialog to Collect Important Patient Information (Theses No. 2022LORR0149). Université de Lorraine. https://hal.univ-lorraine.fr/tel-03889510

Martin, L., Fan, A., Villemonte de la Clergerie, É., Bordes, A., & Sagot, B. (2022). MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases. In LREC 2022 - 13th Language Resources and Evaluation Conference. Marseille, France. https://inria.hal.science/hal-03834719

Martínek, J., Cerisara, C., Král, P., Lenc, L., & Baloun, J. (2022). Weak supervision for Question Type Detection with large language models. In INTERSPEECH 2022 -. Incheon, South Korea. https://hal.science/hal-03786135

Monnin, P., Legrand, J., & Coulet, A. (2022). PGxCorpus and PGxLOD: two shared resources for knowledge management in pharmacogenomics. JOBIM 2022 - Journées Ouvertes en Biologie, Informatique et Mathématiques. https://inria.hal.science/hal-03754888

Scao, T. L., Fan, A., Akiki, C., Pavlick, E., Ilić, S., Hesslow, D., … Wolf, T. (2022). BLOOM: A 176B-Parameter Open-Access Multilingual Language Model. https://inria.hal.science/hal-03850124

Schild, E., Durantin, G., Lamirel, J.-C., & Miconi, F. (2022). Iterative and Semi-Supervised Design of Chatbots Using Interactive Clustering. International Journal of Data Warehousing and Mining (IJDWM), 18(2), 1‑19. https://doi.org/10.4018/IJDWM.298007

2021

Belz, A., Agarwal, S., Shimorina, A., & Reiter, E. (2021). A Systematic Review of Reproducibility Research in Natural Language Processing. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (p. 381‑393). Online, France: Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.eacl-main.29

Benjelloun, I. (2021). Impact du Bruit d’Annotation sur l’Évaluation de Classifieurs (Theses No. 2021LORR0267). Université de Lorraine. https://hal.univ-lorraine.fr/tel-03564063

Brabant, Q., Rojas-Barahona, L. M., & Gardent, C. (2021). Active Learning and Multi-label Classification for Ellipsis and Coreference Detection in Conversational Question-Answering. In 12th International Workshop on Spoken Dialog System Technology (IWSDS 2021). Singapour/Virtual, Singapore. https://hal.science/hal-03533906

Broisin, J., Declercq, C., Fluckiger, C., Parmentier, Y., Peter, Y., & Secq, Y. (2021). Actes de l’atelier APIMU 2021 @ EIAH : Apprendre la Pensée Informatique de la Maternelle à l’Université. Fribourg (virtuel), Switzerland: Julien BROISIN (Université de Toulouse) and Christophe DECLERCQ (INSPÉ de Nantes) and Cédric FLUCKIGER (Université de Lille) and Yannick PARMENTIER (Université de Lorraine) and Yvan PETER (Université de Lille) and Yann SECQ (Université de Lille); HAL. https://hal.science/hal-03241714

Caillon, P., & Cerisara, C. (2021). Growing Neural Networks Achieve Flatter Minima. In ICANN 2021 - 30th International Conference on Artificial Neural Networks (Vol. 12892, p. 222‑234). Bratislava, Slovakia: Springer International Publishing. https://doi.org/10.1007/978-3-030-86340-1\_18

Cerisara, C., Caillon, P., & Le Berre, G. (2021). Unsupervised post-tuning of deep neural networks. In IJCNN. Virtual Event, United States. https://hal.science/hal-02022062

Cerisara, C., & Cuzzocrea, A. (2021). Unsupervised Risk for Privacy. In IEEE BigData, Special Session on Privacy and Security of Big Data. Orlando (virtual), United States. https://hal.science/hal-03407454

Chaoub, A., Voisin, A., Cerisara, C., & Iung, B. (2021). Learning representations with end-to-end models for improved remaining useful life prognostic. In European Conference of the Prognostics and Health Management Society (Vol. 6). Virtual event, Italy. https://hal.science/hal-03247997

Cripwell, L., Legrand, J., & Gardent, C. (2021). Discourse-Based Sentence Splitting. In EMNLP 2021 The 2021 Conference on Empirical Methods in Natural Language Processing (p. 1530‑1540). Punta Cana, Dominican Republic: Association for Computational Linguistics. https://hal.science/hal-03461298

Dugué, N., Lamirel, J.-C., & Chen, Y. (2021). Evaluating clustering quality using features salience: a promising approach. Neural Computing and Applications, 33(19), 12939‑12956. https://doi.org/10.1007/s00521-021-05942-7

Faille, J., Gatt, A., & Gardent, C. (2021). Entity-Based Semantic Adequacy for Data-to-Text Generation. In C. Shivade, R. Gangadharaiah, S. Gella, S. Konam, S. Yuan, Y. Zhang, … B. Wallace (Éd.), Proceeddings of the 2021 Conference on Empirical Methods in Natural Language Processing (p. 1530‑1540). Punta Cana, Dominican Republic: Association for Computational Linguistics. https://hal.science/hal-03461309

Fan, A. (2021). Text Generation with and without Retrieval (Theses No. 2021LORR0164). Université de Lorraine. https://hal.univ-lorraine.fr/tel-03542634

Fan, A., Gardent, C., Braud, C., & Bordes, A. (2021). Augmenting Transformers with KNN-Based Composite Memory for Dialog. Transactions of the Association for Computational Linguistics, 9. https://doi.org/10.1162/tacl\_a\_00356

Gehrmann, S., Adewumi, T., Aggarwal, K., Ammanamanchi, P. S., Aremu, A., Bosselut, A., … Zhou, J. (2021). The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics. In Proceedings of the 1st Workshop on Natural Language Generation, Evaluation, and Metrics (GEM 2021) (p. 96‑120). Online, France: Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.gem-1.10

Gontier, F., Serizel, R., & Cerisara, C. (2021). Automated audio captioning by fine-tuning bart with audioset tags. In DCASE 2021 - 6th Workshop on Detection and Classification of Acoustic Scenes and Events. Virtual, Spain. https://inria.hal.science/hal-03522488

Hafiane, W., Legrand, J., Toussaint, Y., & Coulet, A. (2021). Expérimentations autour des architectures d’apprentissage par transfert pour l’extraction de relations biomédicales. In EGC 2021 - 21ème édition de la conférence “Extraction et Gestion des Connaissances”. Montpellier / Virtuel, France. https://inria.hal.science/hal-03073601

Lamirel, J.-C., Gueddari, Y., Wang, Y., Cuxac, P., Perez, A., & Dugué, N. (2021). Analysis of the dynamics and influence of the research work of Prof. Liu Zeyuan in China featuring a new hybrid approach combining community detection with topic tracking. Scientometrics, 126(7), 6273‑6300. https://doi.org/10.1007/s11192-021-04010-0

Legrand, J., Toussaint, Y., Raïssi, C., & Coulet, A. (2021). Syntax-based transfer learning for the task of biomedical relation extraction. Journal of Biomedical Semantics, 12(1). https://doi.org/10.1186/s13326-021-00248-y

Liednikova, A., Jolivet, P., Durand-Salmon, A., & Gardent, C. (2021). Gathering Information and Engaging the User ComBot : A Task-Based, Serendipitous Dialog Model for Patient-Doctor Interactions. In C. Shivade, R. Gangadharaiah, S. Gella, S. Konam, S. Yuan, Y. Zhang, … B. Wallace (Éd.), NLPMC 2021 - Second Workshop on Natural Language Processing for Medical Conversations (p. 21‑29). Mexico, Mexico: Association for Computational Linguistics. https://hal.science/hal-03461330

Martin, L., Fan, A., Villemonte de La Clergerie, E., Bordes, A., & Sagot, B. (2021). Multilingual Unsupervised Sentence Simplification. https://inria.hal.science/hal-03109299

Martínek, J., Cerisara, C., Král, P., & Lenc, L. (2021). Cross-Lingual Approaches for Task-Specific Dialogue Act Recognition. In I. Maglogiannis, J. Macintyre, & L. Iliadis (Éd.), 17th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI) (Vol. AICT–627, p. 232‑242). Hersonissos, Crete, Greece: Springer International Publishing. https://doi.org/10.1007/978-3-030-79150-6\_19

Parmentier, Y., & Kirchmeyer, S. (2021). Donner du sens à l’objet numérique dans la formation des futur×e×s professeur×e×s des écoles. In J. Broisin, C. Declercq, C. Fluckiger, Y. Parmentier, Y. Peter, & Y. Secq (Éd.), Atelier «  Apprendre la Pensée Informatique de la Maternelle à l’Université  », dans le cadre de la conférence Environnements Informatiques pour l’Apprentissage Humain (EIAH) (p. 34‑45). Fribourg/Virtuel, Switzerland. https://hal.science/hal-03241686

Prouteau, T., Connes, V., Dugué, N., Perez, A., Lamirel, J.-C., Camelin, N., & Meignier, S. (2021). SINr: Fast Computing of Sparse Interpretable Node Representations is not a Sin! In Advances in Intelligent Data Analysis XIX, 19th International Symposium on Intelligent Data Analysis, IDA 2021 (p. 325‑337). Porto, Portugal: Springer, Cham. https://doi.org/10.1007/978-3-030-74251-5\_26

Schild, E., Durantin, G., & Lamirel, J.-C. (2021). Concevoir un assistant conversationnel de manière itérative et semi-supervisée avec le clustering interactif. In Atelier - Fouille de Textes - Text Mine 2021 - En conjonction avec EGC 2021. Montpellier / Virtual, France: Association EGC. https://inria.hal.science/hal-03133060

Schild, E., Durantin, G., Lamirel, J.-C., & Miconi, F. (2021). Conception itérative et semi-supervisée d’assistants conversationnels par regroupement interactif des questions. In EGC 2021 - 21èmes Journées Francophones Extraction et Gestion des Connaissances (Vol. RNTI E–37). Montpellier / Virtual, France: Association EGC; Edition RNTI. https://inria.hal.science/hal-03133007

Shimorina, A. (2021). Natural Language Generation : From Data Creation to Evaluation via Modelling (Theses No. 2021LORR0080). Université de Lorraine. https://hal.univ-lorraine.fr/tel-03254708

Shimorina, A., Parmentier, Y., & Gardent, C. (2021). An Error Analysis Framework for Shallow Surface Realisation. Transactions of the Association for Computational Linguistics, 9, 429‑446. https://doi.org/10.1162/tacl\_a\_00376

Stock, P., Fan, A., Graham, B., Grave, E., Gribonval, R., Jegou, H., & Joulin, A. (2021). Training with Quantization Noise for Extreme Model Compression. In ICLR 2021 - International Conference on Learning Representations. Vienna, Austria. https://inria.hal.science/hal-03136442

2020

Busana, G., Denis, B., Duflot-Kremer, M., Higuet, S., Kataja, L., Kreis, Y., … Weinberger, A. (2020). PIAF : développer la Pensée Informatique et Algorithmique dans l’enseignement Fondamental. In Didapro 8 – DidaSTIC – L’informatique, objets d’enseignements – enjeux épistémologiques, didactiques et de formation. Lille, France. https://hal.science/hal-02463940

Candito, M., Constant, M., Ramisch, C., Savary, A., Guillaume, B., Parmentier, Y., & Cordeiro, S. R. (2020). A French corpus annotated for multiword expressions and named entities. Journal of Language Modelling, 8(2), 415‑479. https://doi.org/10.15398/jlm.v8i2.265

Cerisara, C. (2020). On unsupervised-supervised risk and one-class neural networks. https://hal.science/hal-03037486

Colin, É. (2020). Traitement automatique des langues et génération automatique d’exercices de grammaire (Theses No. 2020LORR0059). Université de Lorraine. https://hal.univ-lorraine.fr/tel-02949349

Ducret, J., Claire, C., Charlot, A., Ameziane, X., & Cruz-Lara, S. (2020). Morpheus: a platform for the representation, manipulation and secure access of standardized morphological data for the digital age textile industry. In 11th 3DBody.Tech Conference & Expo The 11th International Conference and Exhibition on 3D Body Scanning and Processing Technologies. Lugano, Switzerland. https://inria.hal.science/hal-02966114

Faille, J., Gatt, A., & Gardent, C. (2020). The Natural Language Generation Pipeline, Neural Text Generation and Explainability. In 2nd Workshop on Interactive Natural Language Technology for Explainable Artificial Intelligence. Dublin (online), Ireland. https://hal.science/hal-03046206

Fan, A., & Gardent, C. (2020). Multilingual AMR-to-Text Generation. In 2020 Conference on Empirical Methods in Natural Language Processing. Punta Cana, Dominican Republic. https://hal.science/hal-02999676

Ferreira, T. C., Gardent, C., Ilinykh, N., Der Lee, C. van, Mille, S., Moussallem, D., & Shimorina, A. (2020). The 2020 Bilingual, Bi-Directional WebNLG+ Shared Task Overview and Evaluation Results (WebNLG+ 2020). In Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+). Dublin/Virtual, Ireland. https://hal.science/hal-03148418

Ferreira, T. C., Gardent, C., Ilinykh, N., Lee, C. van D., Mille, S., Moussallem, D., & Shimorina, A. (2020). Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+). In WebNLG+: 3rd Workshop on Natural Language Generation from the Semantic Web. Virtuel, Ireland. https://hal.science/hal-03562633

Lamirel, J.-C. (2020a). Apport de la méthode de maximisation des traits pour la fouille de texte. In EGC-2020 – Workshop DL for NLP: Deep Learning pour le traitement automatique des langues. Bruxelles, Belgium. https://inria.hal.science/hal-03180569

Lamirel, J.-C. (2020b). Feature maximization: a new large-scope metric especially adapted to big, noisy and complex data statistics. In 14th International Conference on Operations Research (ICOR 2020). La Havane, Cuba. https://inria.hal.science/hal-03180582

Lamirel, J.-C. (2020c). Mining scientific publications with automated tools. In International Virtual Conference on “Preparedness of Library and Information Services in New Normal”. Mhow/Virtual, India. https://inria.hal.science/hal-03180586

Lamirel, J.-C. (2020d). Text Mining Methods applied to the Processing of Scientific Data. In 9th International Library Information Professional Summit (I-LIPS). Gwalior, India. https://inria.hal.science/hal-03180577

Lamirel, J.-C. (2020e). Use of Advanced AI Technique in Scientific Outputs and Communications Analysis (Part 2). In Invited Seminar – Faculty of Management and Economics & Scientific Association of the Department of Knowledge and Information Science. Téhéran, Iran. https://inria.hal.science/hal-03180600

Lamirel, J.-C. (2020f). Use of Advanced AI Technique in Scientific Outputs and Communications Analysis (Part1). In Invited Seminar – Faculty of Management and Economics & Scientific Association of the Department of Knowledge and Information Science. Téhéran, Iran. https://inria.hal.science/hal-03180593

Lamirel, J.-C., Chen, Y., Cuxac, P., Al Shehabi, S., Dugué, N., & Liu, Z. (2020). Science of Science research in mainland China: 40 years of evolution. A new method of analysis based on clustering with feature maximization and contrast graphs. Scientometrics, 125, 2971‑2999. https://doi.org/10.1007/s11192-020-03503-8

Lamirel, J.-C., Cottrell, M., Olteanu, M., & Lévy, B. (2020a). Editorial of Special Issue on WSOM+ 2017. Neural Computing and Applications, 32, 17973‑17975. https://doi.org/10.1007/s00521-020-05481-7

Lamirel, J.-C., Cottrell, M., Olteanu, M., & Lévy, B. (2020b). Special Issue on WSOM+ 2017. Springer Verlag. https://inria.hal.science/hal-03196372

Lamirel, J.-C., & Cuxac, P. (2020). La recherche en Science de la Science en Chine continentale : 40 ans d’évolution. Une nouvelle méthode d’analyse basée sur le clustering avec maximisation des traits et graphes de contraste. Revue ouverte d’ingénierie des systèmes d’information, 1(1). https://doi.org/10.21494/ISTE.OP.2020.0490

Lamiroy, B. (2020). Formal Performance Evaluation for Document Image Analysis. In International Conference on Computer Science and Computational Intelligence (ICCSCI) (Vol. 179, p. 2). online, Indonesia. https://doi.org/10.1016/j.procs.2021.01.088

Le Berre, G., & Cerisara, C. (2020). Seq-to-NSeq model for multi-summary generation. In ESANN 2020. Bruges, Belgium. https://hal.science/hal-02902734

Le, H. T., Cerisara, C., & Gardent, C. (2020). Quality of syntactic implication of RL-based sentence summarization. In AAAI Workshop on Engineering Dependable and Secure Machine Learning Systems 2020. New York, United States. https://hal.science/hal-02883327

Le, T.-H. (2020). Neural Methods for Sentiment Analysis and Text Summarization (Theses No. 2020LORR0037). Université de Lorraine. https://hal.univ-lorraine.fr/tel-02929745

Legrand, J., Gogdemir, R., Bousquet, C., Dalleau, K., Devignes, M.-D., Digan, W., … Coulet, A. (2020). PGxCorpus, a manually annotated corpus for pharmacogenomics. Scientific Data , 7, 3. https://doi.org/10.1038/s41597-019-0342-9

Liednikova, A., Jolivet, P., Durand-Salmon, A., & Gardent, C. (2020). Learning Health-Bots from Training Data that was Automatically Created using Paraphrase Detection and Expert Knowledge. In Proceedings of the 28th Conference on Computational Linguistics. Barcelona, Spain. https://hal.science/hal-03020294

Mickus, T., Constant, M., & Paperno, D. (2020). Génération automatique de définitions pour le français. In C. Benzitoun, C. Braud, L. Huber, D. Langlois, S. Ouni, S. Pogodalla, & S. Schneider (Éd.), 6e conférence conjointe Journées d’Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 2 : Traitement Automatique des Langues Naturelles (p. 66‑80). Nancy, France: ATALA. https://hal.science/hal-02784756

Parmentier, Y., Reuter, R., Higuet, S., Kataja, L., Kreis, Y., Duflot-Kremer, M., … Denis, B. (2020). PIAF: Developing Computational and Algorithmic Thinking in Fundamental Education. In AACE 2020 - EdMedia + Innovate Learning (Vol. 1, p. 315‑322). Amsterdam / Virtual, Netherlands: Association for the Advancement of Computing in Education (AACE), Waynesville, NC. https://hal.science/hal-02888504

Poibeau, T., Parmentier, Y., & Schang, E. (2020). Actes des 2èmes journées scientifiques du Groupement de Recherche Linguistique Informatique Formelle et de Terrain (LIFT). CNRS. https://hal.science/hal-03066031

Ribeiro, L. F. R., Zhang, Y., Gardent, C., & Gurevych, I. (2020). Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs. Transactions of the Association for Computational Linguistics, 8. https://doi.org/10.1162/tacl\_a\_00332

Rigaud, E. (2020). Représentation vectorielle de paires de verbes pour la prédiction de relations lexicales. In C. Benzitoun, C. Braud, L. Huber, D. Langlois, S. Ouni, S. Pogodalla, & S. Schneider (Éd.), 6e conférence conjointe Journées d’Études sur la Parole (JEP, 33e édition), Traitement Automatique des Langues Naturelles (TALN, 27e édition), Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RÉCITAL, 22e édition). Volume 3 : Rencontre des Étudiants Chercheurs en Informatique pour le TAL (p. 179‑192). Nancy, France: ATALA. https://hal.science/hal-02786199

Shimorina, A. (2020). Human vs Automatic Metrics: on the Importance of Correlation Design. https://hal.science/hal-02459994

2019

Busana, G., Denis, B., Duflot-Kremer, M., Higuet, S., Kataja, L., Kreis, Y., … Weinberger, A. (2019). PIAF : développer la Pensée Informatique et Algorithmique dans l’enseignement Fondamental. https://hal.science/hal-02424418

Colin, E., & Gardent, C. (2019). Generating Text from Anonymised Structures. In Proceedings of the 12th International Conference on Natural Language Generation (p. 112‑117). Hong Kong, China. https://hal.science/hal-02460312

Cuxac, P., Lamirel, J.-C., & Kieffer, N. (2019). SKEEFT : indexing method taking into account the structure of the document. In 15th International Conference on Webometrics, Informetrics and Scientometrics and 20th COLLNET meeting. Dalian, China. https://inria.hal.science/hal-03179724

Fan, A., Gardent, C., Braud, C., & Bordes, A. (2019). Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs. In 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing. Hong Kong, China. https://doi.org/10.18653/v1/D19-1428

Huber, L., Toussaint, Y., Roze, C., Dargnat, M., & Braud, C. (2019a). Alignement de Structures Argumentatives et Discursives par Fouille de Graphes et de Redescriptions. In SFC 2019 - XXVIe Rencontres de la Société Francophone de Classification. Nancy, France. https://hal.science/hal-02266623

Huber, L., Toussaint, Y., Roze, C., Dargnat, M., & Braud, C. (2019b). Aligning Discourse and Argumentation Structures using Subtrees and Redescription Mining. In 6th International Workshop on Argument Mining. Florence, Italy. https://hal.science/hal-02165048

Iruskieta, M., & Braud, C. (2019). EusDisParser: improving an under-resourced discourse parser with cross-lingual data. In Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019 (p. 62‑71). Minneapolis, United States: Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-2709

Lamirel, J.-C. (2019a). A novel approach based on clustering along with feature maximization and contrast graphs. An example of application for diachronic analysis of research. In CICLing 2019 (20th International Conference on Computational Linguistics and Intelligent Text Processing). La Rochelle, France. https://inria.hal.science/hal-03179712

Lamirel, J.-C. (2019b). Adapting feature maximization metric from machine learning to complex network analysis. In IWOR 2019 (13th International Workshop on Operation Research). La Havane, Cuba. https://inria.hal.science/hal-03180516

Lamirel, J.-C. (2019c). Analyse diachronique des données textuelles : mise en comparaison des méthodes LDA et des méthodes basées sur le clustering et les graphes de contraste. In EGC-GAST Workshop 19eme Conference Francophone sur l’extraction et la gestion des connaissances. Metz, France. https://inria.hal.science/hal-03180098

Lamirel, J.-C. (2019d). Basic approaches for text classification. In DUT Invited International Seminar. Dalian, China. https://inria.hal.science/hal-03180526

Lamirel, J.-C. (2019e). Deep learning methods for text classification. In DUT Invited International Seminar. Dalian, China. https://inria.hal.science/hal-03180533

Lamirel, J.-C. (2019f). Diachronic Analysis of Textual Data. In IEEE Congress on Evolutionary Computation, CEC 2019. Wellington, New Zealand. https://inria.hal.science/hal-03180540

Lamirel, J.-C. (2019g). Future Digital Libraries will heavily rely on Machine Learning. In 8th International Library and Information Professionals Summit, (I-LIPS 2019) on Empowering Libraries with emerging Technologies for Common Sustainable Future. Lucknow, India. https://inria.hal.science/hal-03180561

Lamirel, J.-C. (2019h). Methods for Diachronic Analysis of Scientific Data. In Conference on Scientometrics & Evaluation (CCSE2019). Chengdu, China. https://inria.hal.science/hal-03180548

Lamirel, J.-C. (2019i). New approaches for social network analysis. In ICoASL 2019 (Sixth International Conference of Asian Special Libraries). Delhi, India. https://inria.hal.science/hal-03180499

Lamirel, J.-C. (2019j). Une nouvelle approche d’analyse non supervisée des données textuelles basée sur la combinaison du clustering, de la maximisation des traits et des graphes de contraste: application à l’analyse de l’évolution de sujets de recherche en Science de la Science. In Text Mine Workshop 2019 (EGC). Metz, France. https://inria.hal.science/hal-03179710

Lamirel, J.-C. (2019k). Urban segregation analysis in GIS: a new challenge for clustering. In 15th IEEE International Conference: Beyond Databases, Architectures and Structures (BDAS‘2019). Ustron, Poland. https://inria.hal.science/hal-03180537

Lamirel, J.-C. (2019l). Use of data mining and big data management in library science: new challenging approaches. In DELNET (Developing Library Network) Invited Conference. Delhi, India. https://inria.hal.science/hal-03180510

Lamirel, J.-C., & Cuxac, P. (2019a). Feature selection and graph representation for an analysis of science fields evolution : an application to the digital library ISTEX. In ECIR 2019 - 8th International Workshop on Bibliometric-enhanced Information Retrieval (BIR 2019) (Vol. 2345, p. 88‑99). Cologne, France. https://inria.hal.science/hal-03179715

Lamirel, J.-C., & Cuxac, P. (2019b). From massive databases to the Web of data: disambiguation and alignment of geographical entities in scientific texts. In 15th International Conference on Webometrics, Informetrics and Scientometrics and 20th COLLNET meeting. Dalian, China. https://inria.hal.science/hal-03180542

Le, H. T., Cerisara, C., & Gardent, C. (2019). RL extraction of syntax-based chunks for sentence compression. In ICANN 2019 (p. 337‑347). Munich, Germany: Springer International Publishing. https://hal.science/hal-02323821

Martínek, J., Kral, P., Lenc, L., & Cerisara, C. (2019). Multi-Lingual Dialogue Act Recognition with Deep Learning Methods. In Interspeech 2019. Graz, Austria. https://doi.org/10.21437/Interspeech.2019-1691

Muller, P., Braud, C., & Morey, M. (2019). ToNy: Contextual embeddings for accurate multilingual discourse segmentation of full documents. In Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019 (p. 115‑124). Minneapolis, United States: Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-2715

Nourtel, H., Cerisara, C., & Cruz-Lara, S. (2019). Deep unsupervised system log monitoring. In PROFES 2019 - 20th International Conference on Product-Focused Software Process Improvement. Barcelona, Spain. https://hal.science/hal-02295951

Olteanu, M., & Lamirel, J.-C. (2019). When clustering the multiscalar fingerprint of the city reveals its segregation patterns. In 13th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization. Barcelone, Spain. https://inria.hal.science/hal-03179721

Puzikov, Y., Gardent, C., Dagan, I., & Gurevych, I. (2019). Revisiting the Binary Linearization Technique for Surface Realization. Proceedings of The 12th International Conference on Natural Language Generation, 268‑278. https://hal.science/hal-02460309

Ribeiro, L. F. R., Gardent, C., & Gurevych, I. (2019). Enhancing AMR-to-Text Generation with Dual Graph Representations. In 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (Vol. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP–IJCNLP), p. 3181‑3192). Hong Kong, China. https://doi.org/10.18653/v1/D19-1314

Roze, C., Braud, C., & Muller, P. (2019). Which aspects of discourse relations are hard to learn? Primitive decomposition for discourse relation classification. In 20th Annual SIGdial Meeting on Discourse and Dialogue (2019) (p. 432‑441). Stockholm, Sweden: ACL: Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-5950

Shimorina, A., & Gardent, C. (2019a). LORIA / Lorraine University at Multilingual Surface Realisation 2019. In Proceedings of the 2nd Workshop on Multilingual Surface Realisation (MSR 2019) (p. 88‑93). Hong Kong, Hong Kong SAR China: Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-6312

Shimorina, A., & Gardent, C. (2019b). Surface Realisation Using Full Delexicalisation. In 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (p. 3084‑3094). Hong Kong, China. https://doi.org/10.18653/v1/D19-1305

Shimorina, A., Khasanova, E., & Gardent, C. (2019). Creating a Corpus for Russian Data-to-Text Generation Using Neural Machine Translation and Post-Editing. In Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing (p. 44‑49). Florence, Italy: Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-3706

Tsukanova, A., Douros, I. K., Shimorina, A., & Laprie, Y. (2019). Can static vocal tract positions represent articulatory targets in continuous speech? Matching static MRI captures against real-time MRI for the French language. In ICPhS 2019 - International Congress of Phonetic Sciences. Melbourne, Australia. https://inria.hal.science/hal-02181314

2018

Al Saied, H., Dugué, N., & Lamirel, J.-C. (2018). Automatic summarization of scientific publications using a feature selection approach. International Journal on Digital Libraries, 19(2-3), pp 203‑215. https://doi.org/10.1007/s00799-017-0214-x

Al Shehabi, S., Al-Jibouri, A., & Lamirel, J.-C. (2018). Clustering models for mining association rules from numerical datasets. In 1st International Eurasian Conference on Science, Engineering and Technology (EurasianSciEnTech18). Ankara, Turkey. https://inria.hal.science/hal-03179702

Ben Khelil, C., Zribi, C., Duchier, D., & Parmentier, Y. (2018a). A semi-automatically generated TAG for Arabic: Dealing with linguistic phenomena. In 19th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing 2018). Hanoi, Vietnam. https://hal.science/hal-01762597

Ben Khelil, C., Zribi, C., Duchier, D., & Parmentier, Y. (2018b). Building a syntactic-semantic interface for a semi-automatically generated TAG for Arabic. The international Arab journal of information technology, 15(3A), 540‑549. https://hal.science/hal-01809771

Ben Khelil, C., Zribi, C., Duchier, D., & Parmentier, Y. (2018c). Interface syntaxe-sémantique au moyen d’une grammaire d’arbres adjoints pour l’étiquetage sémantique de l’arabe. In 25e conférence sur le Traitement Automatique des Langues Naturelles (TALN). Rennes, France. https://hal.science/hal-01762605

Cerisara, C., Jafaritazehjani, S., Oluokun, A., & Le, H. T. (2018). Multi-task dialog act and sentiment recognition on Mastodon. In COLING. Santa Fe, United States. https://hal.science/hal-01838323

Cerisara, C., Kral, P., & Lenc, L. (2018). On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition. Computer Speech and Language, 47, 175‑193. https://doi.org/10.1016/j.csl.2017.07.009

Colin, É., & Gardent, C. (2018). Generating Syntactic Paraphrases. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (p. 937‑943). Brussels, Belgium: Association for Computational Linguistics. https://doi.org/10.18653/v1/D18-1113

Conneau, A., Kruszewski, G., Lample, G., Barrault, L., & Baroni, M. (2018). In ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics (Vol. 1, p. 2126‑2136). Melbourne, Australia: Association for Computational Linguistics. https://hal.science/hal-01898412

Dugué, N., Lamirel, J.-C., & Perez, A. (2018). Bringing a Feature Selection Metric from Machine Learning to Complex Networks. In COMPLEX NETWORKS 2018:The Seventh International Conference on Complex Networks & their Applications (p. 107‑118). Cambridge, United Kingdom: springer. https://doi.org/10.1007/978-3-030-05414-4\_9

Flores, J. G., Meza, I., Colin, É., Gardent, C., Gangemi, A., & Pineda, L. (2018). Robot Experience Stories: first person generation of robotic task narratives in SitLog. Journal of Intelligent and Fuzzy Systems, 34(5), 3291‑3300. https://doi.org/10.3233/JIFS-169511

Fort, K., Guillaume, B., Constant, M., Lefèbvre, N., & Pilatte, Y.-A. (2018). “Fingers in the Nose”: Evaluating Speakers’ Identification of Multi-Word Expressions Using a Slightly Gamified Crowdsourcing Platform. In Proceedings of the Joint Workshop on Linguistic Annotation, Multiword Expressions and Constructions (LAW-MWE-CxG-2018) (p. 207‑213). Santa Fe, United States. https://hal.science/hal-01912706

Lamirel, J.-C. (2018a). A new noise-resisting feature-based clustering quality evaluation approach scaling from low to high dimensional data. In COMPSTAT 2018 (23rd International Conference on Computational Statistics). Iasi, Romania. https://inria.hal.science/hal-03179695

Lamirel, J.-C. (2018b). Clustering Quality based on features: an efficient approach. In ICOR (13th International Conference on Operation Research). La Havane, Cuba. https://inria.hal.science/hal-03179694

Lamirel, J.-C. (2018c). Highlighting central roles in scientific communities: towards new indicators and methods. In University of Gliwice Invited International Seminar. Gliwice, Poland. https://inria.hal.science/hal-03180076

Lamirel, J.-C. (2018d). Novel graph-based techniques applied to science evaluation in big data context. In Chinese Academy of Science Invited International Seminar. Pékin, China. https://inria.hal.science/hal-03180073

Lamirel, J.-C. (2018e). Optimal clustering model detection using features salience: a new promising approach for real data context. In 25th International Science Conference on Computer Networks CN2018. Gliwice, Poland. https://inria.hal.science/hal-03180084

Lamirel, J.-C. (2018f). Topic extraction models: a comparison. In DUT Invited International Seminar. Dalian, China. https://inria.hal.science/hal-03180094

Lamirel, J.-C., Chen, Y., & Liu, Z. (2018). An overview on 40 years science of science research topic evolution in China: a novel approach based on clustering and feature maximization. Science of Science and Management of S&T, 12, 28‑45. https://inria.hal.science/hal-03179012

Le, H. T., Cerisara, C., & Denis, A. (2018). Do Convolutional Networks need to be Deep for Text Classification ? In AAAI Workshop on Affective Content Analysis. New Orleans, United States. https://hal.science/hal-01690601

Parmentier, Y. (2018). Enseigner la pensée informatique à l’école primaire : formation initiale et continue des professeurs. In Atelier “Organisation et suivi des activités d’apprentissage de l’informatique : outils, modèles et expériences” RJC-EIAH 2018. Besançon, France. https://hal.science/hal-01762626

Shimorina, A., & Gardent, C. (2018). Handling Rare Items in Data-to-Text Generation. In Proceedings of the 11th International Conference on Natural Language Generation (p. 360‑370). Tilburg University, Netherlands: Association for Computational Linguistics. https://doi.org/10.18653/v1/W18-6543

Shimorina, A., Gardent, C., Narayan, S., & Perez-Beltrachini, L. (2018). WebNLG Challenge: Human Evaluation Results (Technical Report). Loria & Inria Grand Est. https://hal.science/hal-03007072

Song, K., Chen, Y., & Lamirel, J.-C. (2018). A novel patent dataset construction strategy based on machine learning for S&T analysis. In 14th International Conference on Webometrics, Informetrics and Scientometrics and 20th COLLNET meeting. Macao, China. https://inria.hal.science/hal-03179704

2017

Ben Khelil, C., Zribi, C., Duchier, D., & Parmentier, Y. (2017). A new syntactic-semantic interface for ArabTAG an Arabic Tree Adjoining grammar. In The 18th International Arab Conference on Information Technology (ACIT‘2017). Yassmine Hammamet, Tunisia. https://hal.science/hal-01676973

Cuxac, P., Lemaire, V., & Lamirel, J.-C. (2017). TextMine‘17. https://hal.science/hal-04188359

Dugué, N., & Lamirel, J.-C. (2017). Une métrique de sélection de variables appliquée à la centralité et à la détection des rôles communautaires. In 17ème Conférence Extraction et Gestion des Connaissances (EGC 2017) (p. 9‑20). Grenoble, France: Editions MTI. https://hal.science/hal-01504066

Dugué, N., Lamirel, J.-C., & Cuxac, P. (2017). Diachronic’Explorer: Keep track of your clusters ! In S. España, J. Ralyté, & C. Souveyet (Éd.), RCIS (p. 1‑2). Grenoble, France: IEEE. https://doi.org/10.1109/RCIS.2016.7549367

Erata, F., Gardent, C., Gyawali, B., Shimorina, A., Lussaud, Y., Tekinerdogan, B., … Monceaux, A. (2017). ModelWriter: Text and Model-Synchronized Document Engineering Platform. In 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE 2017). Urbana-Champaign, IL, United States. https://inria.hal.science/hal-01581256

Fedorchuk, M., & Lamiroy, B. (2017a). Binary Classifier Evaluation Without Ground Truth. In Ninth International Conference on Advances in Pattern Recognition (ICAPR-2017). Bangalore, India. https://hal.science/hal-01680358

Fedorchuk, M., & Lamiroy, B. (2017b). Statistic Metrics for Evaluation of Binary Classifiers without Ground-Truth. In IEEE First Ukraine Conference on Electrical and Computer Engineering (UKRCON) . Kiev, Ukraine: IEEE. https://inria.hal.science/hal-01563615

Gardent, C., & Perez-Beltrachini, L. (2017). A Statistical, Grammar-Based Approach to Micro-Planning. Computational Linguistics. https://doi.org/10.1162/COLI\_a\_00273

Gardent, C., & Retoré, C. (2017). Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017) - Long papers (Vol. W17–68). Montpellier, France. https://hal.science/hal-01803753

Gardent, C., Shimorina, A., Narayan, S., & Perez-Beltrachini, L. (2017a). Creating Training Corpora for NLG Micro-Planning. In 55th annual meeting of the Association for Computational Linguistics (ACL). Vancouver, Canada. https://inria.hal.science/hal-01623744

Gardent, C., Shimorina, A., Narayan, S., & Perez-Beltrachini, L. (2017b). The WebNLG Challenge: Generating Text from RDF Data. In Proceedings of the 10th International Conference on Natural Language Generation (p. 124‑133). Santiago de Compostela, Spain: Association for Computational Linguistics. https://doi.org/10.18653/v1/W17-3518

Gyawali, B., Shimorina, A., Gardent, C., Cruz-Lara, S., & Mahfoudh, M. (2017). Mapping Natural Language to Description Logic. In ESWC 2017 - Extended Semantic Web Conference. Portoroz, Slovenia. https://doi.org/10.1007/978-3-319-58068-5\_17

Hozhyi, V., & Lamiroy, B. (2017). Clustering of users in social networks by their activity. In IEEE First Ukraine Conference on Electrical and Computer Engineering (UKRCON). Kiev, Ukraine. https://hal.science/hal-01664486

Kretschmer, H., Lamirel, J.-C., & Jain, P. K. (2017). Report of The 12th International Conference on Webometrics, Informetrics and Scientometrics (WIS). Collnet Journal of Scientometrics and Information Management, 11(1), 1‑4. https://doi.org/10.1080/09737766.2017.1292665

Lamirel, J.-C. (2017a). Application de la maximisation des traits aux données volumineuses : graphes de contraste et identification des rôles communautaires dans les graphes. In 6ème Journées EGC «  Big Data Mining and Visualization  ». Lille, France. https://inria.hal.science/hal-03179629

Lamirel, J.-C. (2017b). Clustering principles and methods. In DUT Invited International Seminar. Dalian, China. https://inria.hal.science/hal-03180060

Lamirel, J.-C. (2017c). Clustering quality evaluation: a task that has to deal with a naturally noisy context. In LABELNOISE‘2017 - Label Noise Problems in Statistics, Machine Learning and Classification. Nancy, France. https://inria.hal.science/hal-03180067

Lamirel, J.-C. (2017d). Community role analysis in scientometrics and webometrics: new scale independent approaches. In 6th International Library and Information Professionals Summit, LIPS. dehli, India. https://inria.hal.science/hal-03180042

Lamirel, J.-C. (2017e). Diachronic science analysis. In DUT Invited International Seminar. Dalian, China. https://inria.hal.science/hal-03180059

Lamirel, J.-C. (2017f). Feature maximization metric and its application to large data. In 5th CMM Pucón Symposium: Data Science for Frontier Astronomy, Biology and Medicine. Puerto Varas, Chile. https://inria.hal.science/hal-03180049

Lamirel, J.-C. (2017g). Highlighting central roles in scientific communities: towards new indicators and methods. In International ICSTI conference on Information support of science and education: scientometrics and bibliometric. Moscou, Russia. https://inria.hal.science/hal-03180056

Lamirel, J.-C. (2017h). Identification et analyse automatisée de thèmes récurrents dans la science : les exemples de la théorie des cordes et de la théorie du Big Bang en astronomie. In ACFAS : 85e Congrès de l’ACFAS. Montréal, Canada. https://inria.hal.science/hal-03179687

Lamirel, J.-C. (2017i). The text mining techniques in the big data context. In 13th IEEE International Conference: Beyond Databases, Architectures and Structures (BDAS‘2017). Ustron, Poland. https://inria.hal.science/hal-03180037

Lamirel, J.-C., Cottrell, M., & Olteanu, M. (2017). Proceedings of 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM+) 2017. Vandoeuvre les Nancy, France. https://doi.org/10.1109/WSOM41149.2017

Lamirel, J.-C., Jain, P. K., & Babbar, P. (2017). Trends in Bibliometrics and Scientometrics Studies. https://inria.hal.science/hal-03196343

Lamiroy, B., & Dueire Lins, R. (2017). Graphics Recognition. Current Trends and Challenges. (B. Lamiroy & R. D. Lins, Éd.) (Vol. 9657). Nancy, France: Springer. https://inria.hal.science/hal-01401000

Le, H. T., Cerisara, C., & Denis, A. (2017). Report Transfer Learning of Deep Convolutional Network on Twitter (Research Report). Loria & Inria Grand Est. https://hal.science/hal-01562179

Narayan, S., Gardent, C., Cohen, S. B., & Shimorina, A. (2017). Split and Rephrase. In EMNLP 2017: Conference on Empirical Methods in Natural Language Processing (p. 617‑627). Copenhagen, Denmark. https://inria.hal.science/hal-01623746

Perez-Beltrachini, L., & Gardent, C. (2017). Analysing Data-To-Text Generation Benchmarks. In The 10th International Natural Language Generation conference. Santiago de Compostelle, Spain. https://inria.hal.science/hal-01623832

Retoré, C., & Gardent, C. (2017). Proceedings of the 12th International Conference on Computational Semantics (IWCS 2017) - Short papers. Montpellier, France. https://hal.science/hal-01803755

Xiao, C. (2017). Neural-Symbolic Learning for Semantic Parsing (Theses No. 2017LORR0268). Université de Lorraine. https://theses.hal.science/tel-01699569

Xiao, C., Dymetman, M., & Gardent, C. (2017). Symbolic Priors for RNN-based Semantic Parsing. In *wenty-sixth International Joint Conference on Artificial Intelligence (IJCAI-17) * (p. 4186‑4192). Melbourne, Australia. https://doi.org/10.24963/ijcai.2017/585

2016

Asri, L. E. (2016). Learning the Parameters of Reinforcement Learning from Data for Adaptive Spoken Dialogue Systems (Theses No. 2016LORR0350). Université de Lorraine. https://theses.hal.science/tel-01809184

Cruz-Lara, S., Denis, A. A. J., Bellalem, N., & Bellalem, L. (2016). Handbook on 3D3C Platforms: Applications and Tools for Three Dimensional Systems for Community, Creation and Commerce. In Y. Sivan (Éd.), Handbook on 3D3C Platforms: Applications and Tools for Three Dimensional Systems for Community, Creation and Commerce (p. 507). Springer International Publishing. https://doi.org/10.1007/978-3-319-22041-3

Detienne, F., Baker, M., Fréard, D., Barcellini, F., Denis, A., & Quignard, M. (2016). The Descent of Pluto: Interactive dynamics, specialisation and reciprocity of roles in a Wikipedia debate. International Journal of Human-Computer Studies, vol. 86, pp. 11‑31. https://doi.org/10.1016/j.ijhcs.2015.09.002

Dugué, N., Lamirel, J.-C., & Cuxac, P. (2016a). Diachronic’Explorer : keep track of your clusters ! In RCIS 2016. Grenoble, France. https://hal.science/hal-01340844

Dugué, N., Lamirel, J.-C., & Cuxac, P. (2016b). Visualisation pour la détection d’évolutions dans des corpus de publications scientifiques. Les Cahiers du numérique, 12(4), 157‑184. https://hal.science/hal-01504064

Gyawali, B. (2016). Surface Realisation from Knowledge Bases (Theses No. 2016LORR0004). Universite de Lorraine. https://inria.hal.science/tel-01754499

Lamirel, J.-C. (2016a). Managing Very Large and Highly Multidimensional Data Collections Mining Ad-Hoc Metrics and Related Statistics. In XII IEEE Latin American Summer School on Computational Intelligence - EVIC 2016. Santiago, Chile. https://inria.hal.science/hal-03180030

Lamirel, J.-C. (2016b). Reliable clustering indexes. In IEA-AIE 2016 The 29th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems. Morioka, Japan. https://inria.hal.science/hal-03179679

Lamirel, J.-C. (2016c). Reliable clustering quality estimation from low to high dimensional data. In 11th Workshop on Self-Organizing Maps (WSOM 2016). Houston, United States. https://inria.hal.science/hal-01263883

Lamirel, J.-C. (2016d). Vers une interprétation diachronique du contenu de corpus de données numériques multi-sources : application à l´étude de l´évolution des données scientifiques en ligne. In CIDE 19 - 19ème Colloque International sur le Document Électronique 24-26 Novembre 2016. Athènes, Greece. https://inria.hal.science/hal-03179681

Lamirel, J.-C. (2016e). Visualization for the detection of changes in corpora of scientific papers. In LIPS 2016 - 5th Library and Information Professional Summit – (LIPS 2016) on « From Ownership to Access: Leveraging the Digital Paradigm ». Delhi, India. https://inria.hal.science/hal-03179664

Lamirel, J.-C., Cuxac, P., & Hajlaoui, K. (2016). A Novel Approach to Feature Selection Based on Quality Estimation Metrics. In F. Guillet, B. Pinaud, G. Venturini, & D. A. Zighed (Éd.), Advances in Knowledge Discovery and Management (Vol. 615, p. 121‑140). Springer. https://doi.org/10.1007/978-3-319-45763-5\_7

Lamirel, J.-C., Dugué, N., & Cuxac, P. (2016a). New efficient clustering quality indexes. In International Joint Conference on Neural Networks (IJCNN 2016). Vancouver, Canada. https://hal.science/hal-01350509

Lamirel, J.-C., Dugué, N., & Cuxac, P. (2016b). Performing and Visualizing Temporal Analysis of Large Text Data Issued for Open Sources : Past and Future Methods. In S. Kozielski, D. Mrozek, P. Kasprowski, B. Malysiak-Mrozek, & D. Kostrzewa (Éd.), 12th IEEE International Conference: Beyond Databases, Architectures and Structures (BDAS‘2016) (Vol. 613, p. 56‑76). Ustron, Poland: Springer. https://doi.org/10.1007/978-3-319-34099-9\_4

Lamiroy, B., & Lopresti, D. P. (2016). The DAE Platform: a Framework for Reproducible Research in Document Image Analysis. In M. Colom, B. Kerautret, P. Monasse, & J.-M. Morel (Éd.), 1st Workshop on Reproducible Research in Pattern Recognition (RRPR 2016) (Vol. 10214). Cancun, Mexico: Miguel Colom and Bertrand Kerautret and Pascal Monasse and Jean-Michel Morel; Springer. https://inria.hal.science/hal-01449499

Mahfoudh, M., Forestier, G., & Hassenforder, M. (2016). A Benchmark for Ontologies Merging Assessment. In International Conference on Knowledge Science, Engineering and Management (KSEM) (Vol. 9983, p. 555‑566). Passau, Germany: Springer International Publishing. https://doi.org/10.1007/978-3-319-47650-6\_44

Narayan, S., & Gardent, C. (2016). Unsupervised Sentence Simplification Using Deep Semantics. In* The 9th International Natural Language Generation conference* (p. 111‑120). Edinburgh, United Kingdom. https://doi.org/10.18653/v1/W16-6620

Perez-Beltrachini, L., & Gardent, C. (2016). Learning Embeddings to lexicalise RDF Properties. In *SEM 2016,. The Fifth Joint Conference on Lexical and Computational Semantics. (p. 219‑228). Berlin, Germany. https://doi.org/10.18653/v1/S16-2027

Perez-Beltrachini, L., Sayed, R. M., & Gardent, C. (2016). Building RDF Content for Data-to-Text Generation. In The 26th International Conference on Computational Linguistics (COLING 2016). Osaka, Japan. https://inria.hal.science/hal-01623800

Serrière, G., Cerisara, C., Fohr, D., & Mella, O. (2016). Weakly-supervised text-to-speech alignment confidence measure. In International Conference on Computational Linguistics (COLING). Osaka, Japan. https://hal.science/hal-01378355

Xiao, C., Bouchard, G., Dymetman, M., & Gardent, C. (2016). Orthogonality regularizer for question answering. In* *SEM 2016,. The Fifth Joint Conference on Lexical and Computational Semantics* (p. 142‑147). Berlin, Germany. https://doi.org/10.18653/v1/S16-2019

Xiao, C., Dymetman, M., & Gardent, C. (2016). Sequence-based Structured Prediction for Semantic Parsing. In*Annual meeting of the Association for Computational Linguistics (ACL) * (p. 1341‑1350). Berlin, Germany. https://doi.org/10.18653/v1/P16-1127

2015

Barney Smith, E. H., & Lamiroy, B. (2015). Circle Detection Performance Evaluation Revisited. In B. Lamiroy & R. D. Lins (Éd.), Graphics Recognition. Current Trends and Challenges : 11th IAPR International Workshop on Graphics Recognition, GREC 2015 (Vol. 9657). Nancy, France: Springer. https://doi.org/10.1007/978-3-319-52159-6\_1

Carlier, A., Goyens, M., & Lamiroy, B. (2015). Le français en diachronie: nouveaux objets et méthodes. (A. C. (éd.), M. G. (éd.), & B. L. (éd.), Éd.) (p. 464). Peter Lang. https://hal.univ-lille.fr/hal-01758192

Dugué, N., Tebbakh, A., Cuxac, P., & Lamirel, J.-C. (2015). Feature selection and complex networks methods for an analysis of collaboration evolution in science: an application to the ISTEX digital library. In ISKO-MAGHREB 2015. Hammamet, Tunisia. https://hal.science/hal-01231791

Gardent, C., & Narayan, S. (2015). Multiple Adjunction in Feature-Based Tree-Adjoining Grammar. Computational Linguistics, 41(1), 29. https://doi.org/10.1162/COLI\_a\_00217

Gyawali, B., Gardent, C., & Cerisara, C. (2015a). A Domain Agnostic Approach to Verbalizing n-ary Events without Parallel Corpora. In Proceedings of the 15th European Workshop on Natural Language Generation (ENLG) (p. 18‑27). Brighton, United Kingdom. https://inria.hal.science/hal-01207155

Gyawali, B., Gardent, C., & Cerisara, C. (2015b). Automatic Verbalisation of Biological Events. In International Workshop on Definitions in Ontologies (IWOOD 2015). Lisbon, Portugal. https://inria.hal.science/hal-01214569

Kral, P., Lenc, L., & Cerisara, C. (2015). Semantic Features for Dialogue Act Recognition. In 3rd International Conference on Statistical Language and Speech Processing (SLSP). Budapest, Hungary. https://hal.science/hal-01256301

Lamirel, J.-C. (2015a). Exploring the dynamics of scientific collections using a new combination of approaches mixing graph representation and feature selection. In DISC 2015. Daegu, South Korea. https://inria.hal.science/hal-01263878

Lamirel, J.-C. (2015b). Feature maximization based clustering quality evaluation: a promising approach. In QIMIE 2015: 4th International PAKDD Workshop on Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models. Ho Chi Min, Vietnam. https://inria.hal.science/hal-01263867

Lamirel, J.-C. (2015c). Feature Maximization: a Highly Accurate Approach for Feature Selection and Meta-Classification. In Classification Society 2015 Annual Meeting. Hamilton, Canada. https://inria.hal.science/hal-01263870

Lamirel, J.-C. (2015d). Feature selection an graph representation for an analysis of science fields evolution: an application to digital library ISTEX. https://inria.hal.science/hal-01263830

Lamirel, J.-C. (2015e). Les mots : tenseurs de sons – vecteurs de sens. https://inria.hal.science/hal-01263822

Lamirel, J.-C. (2015g). New metrics and related statistical approaches for efficient mining in very large and highly multidimensional databases. In 11th IEEE International Conference: Beyond Databases, Architectures and Structures (BDAS‘2015). Cracovie, Poland. https://inria.hal.science/hal-01263865

Lamirel, J.-C. (2015f). New metrics and related statistical approaches for efficient mining in very large and highly multidimensional databases. https://inria.hal.science/hal-01263816

Lamirel, J.-C. (2015h). New quality indexes for optimal clustering model identification based on cross-domain approach. In ICTAI – CIMA workshop - 28th International Conference on Tools with Artificial Intelligence (ICTAI). Vietri sul Mare, Italy. https://inria.hal.science/hal-01263872

Lamirel, J.-C. (2015i). Nouveaux indices de qualité de clustering basés sur la maximisation de traits. In SFC‘15 . Nantes, France. https://inria.hal.science/hal-01263871

Lamirel, J.-C., & Cuxac, P. (2015). New quality indexes for optimal clustering model identification with high dimensional data. In ICDM-HDM‘15 - International Workshop on High Dimensional Data Mining. Atlantic City, United States: IEEE. https://doi.org/10.1109/ICDMW.2015.220

Lamirel, J.-C., Falk, I., & Gardent, C. (2015). Federating clustering and cluster labelling capabilities with a single approach based on feature maximization: French verb classes identification with IGNGF neural clustering. Neurocomputing, 147, 136‑146. https://doi.org/10.1016/j.neucom.2014.02.060

Lamiroy, B., & Pierrot, P. (2015). Statistical Performance Metrics for Use with Imprecise Ground-Truth. In B. Lamiroy & R. D. Lins (Éd.), Graphics Recognition. Current Trends and Challenges: 11th International Workshop on Graphics Recognition, GREC 2015 (Vol. 9657). Nancy, France: Springer. https://doi.org/10.1007/978-3-319-52159-6\_3

Mennesson, J., Allaert, B., Bilasco, I. M., Der Aa, N. van, Denis, A. A. J., & Cruz-Lara, S. (2015). Faces and Thoughts: An Empathic Dairy. In IEEE International Conference on Automatic Face and Gesture Recognition. Ljubljana, Slovenia: IEEE. https://hal.science/hal-01150212

Mrabet, Y., Gardent, C., Foulonneau, M., Elena, S., & Eric, R. (2015). Towards Knowledge-Driven Annotation. In Twenty-Ninth AAAI Conference on Artificial Intelligence, AAAI 2015. Austin, United States. https://inria.hal.science/hal-01261551

Rojas Barahona, L. M., & Cerisara, C. (2015a). Enhanced discriminative models with tree kernels and unsupervised training for entity detection. In 6th. International Conference on Information Systems & Economic Intelligence (SIIE). Hammamet, Tunisia. https://hal.science/hal-01184847

Rojas Barahona, L. M., & Cerisara, C. (2015b). Weakly supervised discriminative training of linear models for Natural Language Processing. In 3rd International Conference on Statistical Language and Speech Processing (SLSP). Budapest, Hungary. https://hal.science/hal-01184849

2014

Carlier, A., & Lamiroy, B. (2014a). Development of new grammatical categories: articles and auxiliaries in Romance. In Proceedings Evolang X. Vienne, Austria: KU Leuven. https://hal.univ-lille.fr/hal-01760359

Carlier, A., & Lamiroy, B. (2014b). The grammaticalization of the prepositional partitive in Romance. In T. H. (éd.) & S. L. (éd.) (Éd.), Partitive Cases and Related Categories (p. 477‑519). Mouton-De Gruyter. https://hal.univ-lille.fr/hal-01760164

Cerisara, C. (2014). Semi-supervised experiments at LORIA for the SPMRL 2014 Shared Task. In Proc. of the Shared Task on Statistical Parsing of Morphologically Rich Languages. Dublin, Ireland. https://hal.science/hal-01109886

Cossu, J.-V., Dugué, N., & Labatut, V. (2014). Twitter Influence - Characterization of Twitter Profiles, with an application to offline influence detection (Version 1). https://hal.science/hal-02179513

Cruz-Lara, S., Denis, A., & Bellalem, N. (2014). Linguistic and Multilingual Issues in Virtual Worlds and Serious Games: a General Review. Journal of virtual worlds research, 7(1). https://inria.hal.science/hal-00949908

Denis, A., Cruz-Lara, S., Bellalem, N., & Bellalem, L. (2014a). Synalp-Empathic: A Valence Shifting Hybrid System for Sentiment Analysis. In 8th International Workshop on Semantic Evaluation (SemEval 2014) (p. 605‑609). Dublin, Ireland. https://hal.science/hal-01099671

Denis, A., Cruz-Lara, S., Bellalem, N., & Bellalem, L. (2014b). Visualization of affect in movie scripts. In Empatex, 1st International Workshop on Empathic Television Experiences at TVX 2014. Newcastle, United Kingdom. https://hal.science/hal-01099668

Franconi, E., Gardent, C., Juarez-Castro, X. I., & Perez-Beltrachini, L. (2014). Quelo Natural Language Interface: Generating queries and answer descriptions. In Natural Language Interfaces for Web of Data. Riva del Gada - Trention, Italy. https://hal.science/hal-01109607

Gardent, C. (2014). Syntax and Data-to-Text Generation. In Lecture Notes in Computer Science (Vol. 8791, p. 3‑20). https://doi.org/10.1007/978-3-319-11397-5\_1

Gardent, C., Parmentier, Y., Perrier, G., & Schmitz, S. (2014). Lexical Disambiguation in LTAG using Left Context. In Z. Vetulani & J. Mariani (Éd.), Human Language Technology. Challenges for Computer Science and Linguistics. 5th Language and Technology Conference, LTC 2011, Poznan, Poland, November 25-27, 2011, Revised Selected Papers (Vol. 8387, p. 67‑79). Springer. https://doi.org/10.1007/978-3-319-08958-4\_6

Gyawali, B., & Gardent, C. (2014). Surface Realisation from Knowledge-Bases. In ACL (Éd.), the 52nd Annual Meeting of the Association for Computational Linguistics (p. 424‑434). Baltimore, United States. https://hal.science/hal-01021916

Hajlaoui, K., & Lamirel, J.-C. (2014). A promising combination of approaches for solving complex text classification tasks: application to the classification of scientific papers into patents classes. International Journal of Knowledge and Learning, 9(1), 22. https://inria.hal.science/hal-01263648

Kral, P., & Cerisara, C. (2014). Automatic dialogue act recognition with syntactic features. Language Resources and Evaluation, http://link.springer.com/article/10.1007%2Fs10579-014-9263-6. https://doi.org/10.1007/s10579-014-9263-6

Lamirel, J.-C. (2014a). Feature maximization: a new incremental and flexible approach for the efficient analysis of large and dynamic data collections. https://inria.hal.science/hal-01263803

Lamirel, J.-C. (2014b). Measuring and highlighting changes of influence in authors/topics networks through the use of a new metric: application to a compound dataset of scientific data. In DISC 2014. Daegu, South Korea. https://inria.hal.science/hal-01263864

Lamirel, J.-C., & Cuxac, P. (2014a). Dynamically highlighting influential authors in a topic domain : a tentative approach. In 10th International Conference on Webometrics, Informetrics and Scientometrics (WIS). Illmenau, Germany: TU Ilmenau. https://inria.hal.science/hal-01263850

Lamirel, J.-C., & Cuxac, P. (2014b). Improving textual data classification and discrimination using an ad-hoc metric: application to a famous text discrimination challenge. In 4th International Symposium ISKO-Maghreb 2014 (p. 1‑6). Alger, Algeria: IEEE. https://doi.org/10.1109/ISKO-Maghreb.2014.7033480

Lamirel, J.-C., & Cuxac, P. (2014c). Une nouvelle méthode statistique pour la classification robuste des données textuelles : le cas Mitterand-Chirac. In JADT 2014 : 12èmes Journées internationales d’Analyse statistique des Données Textuelles (p. 337‑349). Paris, France. https://inria.hal.science/hal-01263847

Lamirel, J.-C., Cuxac, P., & Hajlaoui, K. (2014a). Optimizing text classification through efficient feature selection based on quality metric. Journal of Intelligent Information Systems, 18. https://inria.hal.science/hal-01263651

Lamirel, J.-C., Cuxac, P., & Hajlaoui, K. (2014b). Une nouvelle approche pour la sélection de variables basée sur une métrique d’estimation de la qualité. In EGC 2014. Rennes, France. https://inria.hal.science/hal-01263843

Lamirel, J.-C., & Reymond, D. (2014). Automatic websites classification and retrieval using websites communication signatures. Journal of Information Management and Scientometrics. https://inria.hal.science/hal-01263646

Lorenzo, A., & Cerisara, C. (2014). Semi-supervised SRL system with Bayesian inference. In 15th International Conference on Intelligent Text Processing and Computational Linguistics (p. 433). Kathmandu, Nepal. https://hal.science/hal-01015414

Narayan, S. (2014). Generating and Simplifying Sentences (Theses No. 2014LORR0166). Université de Lorraine. https://hal.science/tel-01751063

Narayan, S., & Gardent, C. (2014). Hybrid Simplification using Deep Semantics and Machine Translation. In the 52nd Annual Meeting of the Association for Computational Linguistics (p. 435‑445). Baltimore, United States: ACL. https://hal.science/hal-01109581

Perez-Beltrachini, L., Gardent, C., & Franconi, E. (2014). Incremental Query Generatio. In the 14th Conference of the European Chapter of the Association for Computational Linguistics. (p. 183‑191). Gothenburg, Sweden. https://hal.science/hal-01021917

Rojas Barahona, L. M., & Cerisara, C. (2014). Bayesian Inverse Reinforcement Learning for Modeling Conversational Agents in a Virtual Environment. In Conference on Intelligent Text Processing and Computational Linguistics. Kathmandu, Nepal: Alexander Gelbukh; Springer. https://inria.hal.science/hal-01002361

2013

Banik, E., Gardent, C., & Kow, E. (2013). The KBGen Challenge. In the 14th European Workshop on Natural Language Generation (ENLG) (p. 94‑97). Sofia, Bulgaria. https://hal.science/hal-00920605

Bimbot, F., Cerisara, C., Fougeron, C., Gravier, G., Lamel, L., Pellegrino, F., & Perrier, P. (2013). Proceedings of the 14th Annual Conference of the International Speech Communication Association (Interspeech), 25-29 August 2013, Lyon (France) (p. over 3500 pages). International Speech Communication Association (ISCA). https://hal.science/hal-00931864

Carlier, A., Goyens, M., & Lamiroy, B. (2013). A genitive marker in French ? Its grammaticalization path from Latin to French. In A. C. (éd.) & J.-C. V. (éd.) (Éd.), Genitive Case And Genitive Construction (p. 141‑216). Benjamins. https://hal.univ-lille.fr/hal-01760132

Cerisara, C., Lorenzo, A., & Kral, P. (2013). Weakly supervised parsing with rules. In INTERSPEECH 2013 (p. 2192‑2196). Lyon, France. https://hal.science/hal-00850437

Crabbé, B., Duchier, D., Gardent, C., Le Roux, J., & Parmentier, Y. (2013). XMG : eXtensible MetaGrammar. Computational Linguistics, 39(3), 591‑629. https://hal.science/hal-00768224

Cruz-Lara, S., Fernández Manjón, B., & Vaz de Carvalho, C. (2013). Enfoques Innovadores en Juegos Serios. IEEE VAEP RITA, 1(1), 19‑21. https://inria.hal.science/hal-00820350

Cuxac, P., & Lamirel, J.-C. (2013a). Analyse des évolutions et des interactions entre domaines scientifiques : GRAFSEL, association de la sélection de variables et de la représentation graphique. In VSST 2013 - 7e colloque de Veille Stratégique, Scientifique et Technologique. Nancy, France. https://hal.science/hal-00962312

Cuxac, P., & Lamirel, J.-C. (2013b). Analysis of evolutions and interactions between science fields : the cooperation between feature selection and graph representation. In 14th COLLNET Meeting. Tartu, Estonia. https://hal.science/hal-00959415

Cuxac, P., Lamirel, J.-C., & Bonvallot, V. (2013). Efficient supervised and semi-supervised approaches for affiliations disambiguation. Scientometrics, 97(1), 47‑58. https://doi.org/10.1007/s11192-013-1025-5

Denis, A., Cruz-Lara, S., & Bellalem, N. (2013). General Purpose Textual Sentiment Analysis and Emotion Detection Tools. In Workshop on Emotion and Computing. Koblenz, Germany. https://inria.hal.science/hal-00860316

Falk, I., & Gardent, C. (2013). Combining Formal Concept Analysis and Translation to Assign Frames and Semantic Role Sets to French Verbs. Annals of Mathematics and Artificial Intelligence. https://doi.org/10.1007/s10472-013-9377-3

Gardent, C., Lorenzo, A., Perez-Beltrachini, L., & Rojas-Barahona, L. M. (2013). Weakly and Strongly Constrained Dialogues for Language Learning. In the 14th annual SIGdial Meeting on Discourse and Dialogue SIGDIAL 2013 (p. 357‑359). Metz, France. https://hal.science/hal-00920608

Gardent, C., & Narayan, S. (2013). Generating Elliptic Coordination. In the 14th European Workshop on Natural Language Generation (ENLG) (p. 40‑50). Sofia, Bulgaria. https://hal.science/hal-00920606

Gardent, C., & Rojas Barahona, L. M. (2013). Using Paraphrases and Lexical Semantics to Improve the Accuracy and the Robustness of Supervised Models in Situated Dialogue Systems. In Conference on Empirical Methods in Natural Language Processing (p. 808‑813). Seattle, United States: SIGDAT, the Association for Computational Linguistics special interest group on linguistic data and corpus-based approaches to NLP. https://inria.hal.science/hal-00905405

Gyawali, B., & Gardent, C. (2013). A Hybrid Approach To Generating from the KBGen Knowledge-Base. In the 14th European Workshop on Natural Language Generation (ENLG) (p. 204‑205). Sofia, Bulgaria. https://hal.science/hal-00920607

Hajlaoui, K., Cuxac, P., Lamirel, J.-C., & François, C. (2013). Aide à l’expertise des brevets par alignement avec les publications scientifiques. Document numérique - Revue des sciences et technologies de l’information. Série Document numérique, 16(1), 11‑29. https://doi.org/10.3166/DN.16.1.11-29

Lamirel, J.-C. (2013a). Analysis of evolution and interactions between science fields: the cooperation between feature selection and graph representation. https://inria.hal.science/hal-01263795

Lamirel, J.-C. (2013b). Dealing with highly imbalanced textual data gathered into similar classes. In IJCNN - 2013 International Joint Conference on Neural Networks. Dallas, United States. https://doi.org/10.1109/IJCNN.2013.6707044

Lamirel, J.-C. (2013c). Enhancing classification accuracy with the help of feature maximization metric. In ICTAI. Washington, United States. https://inria.hal.science/hal-00939038

Lamirel, J.-C. (2013d). Enhancing feature selection with feature maximization metric. In WSC. Hong Kong, China. https://inria.hal.science/hal-00939043

Lamirel, J.-C. (2013e). Exploiting feature maximization metric in the framework of webometrics and scientometrics. https://inria.hal.science/hal-01263788

Lamirel, J.-C. (2013f). Multi-View Data Analysis and Concept Extraction Methods for Text. Knowledge Organization, 40(5), 305‑319. https://doi.org/10.5771/0943-7444-2013-5-305

Lamirel, J.-C. (2013g). Nouvelles méthodes statistiques pour le texte. https://inria.hal.science/hal-01263800

Lamirel, J.-C. (2013h). Supervised and unsupervised multi-view data analysis methods for text. In WISSORG‘2013. Postdam, Germany. https://inria.hal.science/hal-00939045

Lamirel, J.-C., & Cuxac, P. (2013a). Amélioration de la qualité des résultats des classifieurs par la métrique de maximisation d’étiquetage. In ISKO-MAGHREB. Marrakech, Morocco. https://inria.hal.science/hal-00939041

Lamirel, J.-C., & Cuxac, P. (2013b). Nouvelles méthodes statistiques pour le traitement des données textuelles volumineuses et changeantes. In Premières Rencontres Scientifiques du Réseau Mixte LaFEF (Langue Française et Expressions Francophones). Strasbourg, France. https://inria.hal.science/hal-00939040

Lamirel, J.-C., Cuxac, P., Hajlaoui, K., & Chivukula, A. S. (2013). A new feature selection and feature contrasting approach based on quality metric: application to efficient classification of complex textual data. In International Workshop on Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE 2013). Gold Coast, Australia. https://hal.science/hal-00960127

Lorenzo, A., Rojas-Barahona, L. M., & Cerisara, C. (2013). Unsupervised structured semantic inference for spoken dialog reservation tasks. In SIGDIAL - 14th annual SIGdial Meeting on Discourse and Dialogue - 2013 (p. 12‑20). Metz, France. https://hal.science/hal-00911017

Perez, L. H. (2013). Natural Language Generation for Language Learning (Theses No. 2013LORR0062). Université de Lorraine. https://inria.hal.science/tel-01749799

2012

Amoia, M., Brétaudière, T., Denis, A., Gardent, C., & Perez-Beltrachini, L. (2012). A Serious Game for Second Language Acquisition in a Virtual Environment. Journal of Systemics, Cybernetics and Informatics, 10(1), 24‑34. https://inria.hal.science/hal-00766460

Banik, E., Gardent, C., Scott, D., Dinesh, N., & Linag, F. (2012). KBGen - Text Generation for Knowledge Bases as a New Shared Task. In The seventh International Natural Language Generation Conference. Starved Rock, Illinois, USA. (p. 141‑146). Starved Rock, Illinois, United States. https://hal.science/hal-00768616

Carlier, A., Mulder, W. de, & Lamiroy, B. (2012). On the Pace of Grammaticalization in Romance. (A. C. (éd.), W. D. M. (éd.), & B. L. (éd.), Éd.). De Gruyter. https://hal.univ-lille.fr/hal-01758139

Cerisara, C., & Lorenzo, A. (2012). Mixed probabilistic and deterministic dependency parsing. In 13th Annual Conference of the International Speech Communication Association - InterSpeech 2012 (p. 4). Portland, United States. https://hal.science/hal-00706547

Cuxac, P., Bonvallot, V., & Lamirel, J.-C. (2012). Efficient supervised and semi-supervised approaches for affliations disambiguation. In 13th COLLNET Meeting (p. 10 p.). Seoul, North Korea. https://hal.science/hal-00956386

Cuxac, P., & Lamirel, J.-C. (2012). Efficient supervised and semi-supervised approaches for affiliations disambiguation. In WIS - 8th International Conference on Webometrics, Informetrics and Scientometrics - 2012. Séoul, South Korea. https://doi.org/10.1007/s11192-013-1025-5

Cuxac, P., Lamirel, J.-C., & Bonvallot, V. (2012). Approche semi-supervisée pour la désambiguïsation des affiliations dans les bases de données bibliographiques. In 2nd International Symposium ISKO Maghreb - 2012. Hammamet, Tunisia. https://inria.hal.science/hal-00781587

Denis, A., Falk, I., Gardent, C., & Perez-Beltrachini, L. (2012). Representation of Linguistic and Domain Knowledge for Second Language Learning in Virtual Worlds. In LREC - The eighth international conference on Language Resources and Evaluation - 2012 (p. 2631‑2635). Istanbul, Turkey. https://inria.hal.science/hal-00766418

Denis, A., Quignard, M., Fréard, D., Détienne, F., Baker, M., & Barcellini, F. (2012). Détection de conflits dans les communautés épistémiques en ligne. In TALN 2012. 19e conférence sur le Traitement Automatique des Langues Naturelles. Grenoble, France. https://inria.hal.science/hal-00766397

Falk, I. (2012). Making Use of Existing Lexical Resources to Build a Verbnet like Classification of French Verbs (Theses). Université Nancy II. https://theses.hal.science/tel-00714737

Falk, I., Gardent, C., & Lamirel, J.-C. (2012). Classifying French Verbs Using French and English Lexical Resources. In The 50th annual meeting of the Association for Computational Linguistics - ACL‘12 (Vol. 1: Long Papers, p. 854‑863). Jeju, South Korea: The Association for Computational Linguistics (ACL); Association for Computational Linguistics. https://inria.hal.science/hal-00690484

Fréard, D., Détienne, F., Baker, M., Barcellini, F., Quignard, M., & Denis, A. (2012). Visualising zones of collaboration in online collective activity: a case study in Wikipedia. In 30th Annual European Conference on Cognitive Ergonomics (ECCE 2012). Edinburgh, United Kingdom. https://doi.org/10.1145/2448136.2448160

Gardent, C., & Kruszewski, G. (2012). Generation for Grammar Engineering. In INLG 2012, The seventh International Natural Language Generation Conference. (p. 31‑40). Starved Rock, Illinois, United States. https://hal.science/hal-00768612

Gardent, C., & Narayan, S. (2012). Error Mining on Dependency Trees. In 50th Annual Meeting of the Association for Computational Linguistics (p. 592‑600). Jeju Island, South Korea. https://hal.science/hal-00768204

Gardent, C., & Perez-Beltrachini, L. (2012). Using FB-LTAG Derivation Trees to Generate Transformation-Based Grammar Exercices. In TAG+11: The 11th International Workshop on Tree Adjoining Grammars and Related Formalisms (p. 117‑125). Paris, France. https://hal.science/hal-00768231

Gillot, C. (2012). Modèles de langue exploitant la similarité structurelle entre séquences pour la reconnaissance de la parole (Theses). Université de Lorraine. https://hal.science/tel-01258153

Hajlaoui, K., Cuxac, P., Lamirel, J.-C., & François, C. (2012a). Aide à l’expertise des brevets par alignement avec les publications scientifiques. In 3ème Séminaire de Veille Stratégique, Scientifique et Technologique. Ajaccio, France. https://hal.science/hal-00959396

Hajlaoui, K., Cuxac, P., Lamirel, J.-C., & François, C. (2012b). Enhancing Patent Expertise through Automatic Matching with Scientific Papers. In J.-G. Ganascia, P. Lenca, & J.-M. Petit (Éd.), DS 2012 : The Fifteenth International Conference on Discovery Science (Vol. 7569, p. 299‑312). Lyon, France: Springer. https://doi.org/10.1007/978-3-642-33492-4\_24

Lamirel, J.-C. (2012a). A new approach for automatizing the analysis of research topics dynamics: application to optoelectronics research. Scientometrics, 93(1), 151‑166. https://doi.org/10.1007/s11192-012-0771-0

Lamirel, J.-C. (2012b). A new approach for improving clustering quality based on connected maximized cluster features. In Classification Society 2012 Annual Meeting. Pittsburgh, United States. https://inria.hal.science/hal-00781580

Lamirel, J.-C. (2012c). A new approach for improving clustering quality based on connected maximized cluster features. https://inria.hal.science/hal-01263775

Lamirel, J.-C. (2012d). A new incremental clustering approach based on cluster data feature maximization. In Classification Society 2012 Annual Meeting. Pittsburgh, United States. https://inria.hal.science/hal-00781579

Lamirel, J.-C. (2012e). A new incremental clustering approach based on cluster data feature maximization. https://inria.hal.science/hal-01263778

Lamirel, J.-C. (2012f). An unbiased symbolico-numeric approach for reliable clustering quality evaluation. In Classification Society 2012 Annual Meeting. Pittsburgh, United States. https://inria.hal.science/hal-00781578

Lamirel, J.-C. (2012g). An unbiased symbolico-numeric approach for reliable clustering quality evaluation. https://inria.hal.science/hal-01263781

Lamirel, J.-C. (2012h). Combining Neural Clustering with Intelligent Labeling and Unsupervised Bayesian Reasoning in a Multiview Context for Efficient Diachronic Analysis. In WSOM - 9th Workshop on Self-Organizing Maps - 2012. Santiago, Chile. https://inria.hal.science/hal-00781588

Lamirel, J.-C. (2012i). Opening new perspectives for classifying and mining textual and web data. In 2nd international Symposium ISKO-MAGHREB - 2012. Hammamet, Tunisia. https://inria.hal.science/hal-00781577

Lamirel, J.-C. (2012j). Opening new perspectives for classifying and mining textual and web data. https://inria.hal.science/hal-01263783

Lamirel, J.-C., & Cuxac, P. (2012). Détection des évolutions dans les corpus textuels. In EGC 2012 CIDN Workshop. Bordeaux, France. https://inria.hal.science/hal-00781582

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