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Comparison of Text Mining Models for Food and Dietary Constituent Named-Entity Recognition
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In: Machine Learning and Knowledge Extraction; Volume 4; Issue 1; Pages: 254-275 (2022)
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SENTIMENT ANALYSIS WITH NEURAL NETWORK ; СЕНТИМЕНТ АНАЛІЗ ЗАСОБАМИ НЕЙРОННОЇ МЕРЕЖІ
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In: Математичне моделювання; № 1(44) (2021); 30-37 ; 2519-8114 ; 2519-8106 (2021)
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Can we Generate Emotional Pronunciations for Expressive Speech Synthesis?
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In: ISSN: 1949-3045 ; IEEE Transactions on Affective Computing ; https://hal.archives-ouvertes.fr/hal-01802463 ; IEEE Transactions on Affective Computing, Institute of Electrical and Electronics Engineers, 2020, 11 (4), pp.684-695. ⟨10.1109/TAFFC.2018.2828429⟩ (2020)
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Morphosyntactic disambiguation and segmentation for historical Polish with graph-based conditional random fields
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In: 21st International Conference on Text, Speech and Dialogue (TSD 2018) ; https://hal.archives-ouvertes.fr/hal-01835573 ; 21st International Conference on Text, Speech and Dialogue (TSD 2018), Sep 2018, Brno, Czech Republic (2018)
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Dialog Acts Annotations for Online Chats ; Annotation en Actes de Dialogue pour les Conversations d’Assistance en Ligne
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In: Actes TALN-RECITAL 2018 ; 25e conférence sur le Traitement Automatique des Langues Naturelles (TALN) ; https://hal.archives-ouvertes.fr/hal-01943345 ; 25e conférence sur le Traitement Automatique des Langues Naturelles (TALN), 2018, Rennes, France (2018)
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Semantic reranking of CRF label sequences for verbal multiword expression identification
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In: Moreau, Erwan, Alsulaimani, Ashjan, Maldonado, Alfredo orcid:0000-0001-8426-5249 , Han, Lifeng, Vogel, Carl orcid:0000-0001-8928-8546 and Dutta Chowdhury, Koel (2018) Semantic reranking of CRF label sequences for verbal multiword expression identification. In: Markantonatou, Stella, Ramisch, Carlos orcid:0000-0001-7466-9039 , Savary, Agata and Vincze, Veronika orcid:0000-0002-9844-2194 , (eds.) Multiword expressions at length and in depth: Extended papers from the MWE 2017 workshop. Language Science Press, Berlin, pp. 177-207. ISBN 978-3-96110-124-5 (2018)
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Abstract:
Verbal multiword Expressions (VMWE) identification can be addressed successfully as a sequence labeling problem via conditional random fields (CRFs) by returning the one label sequence with maximal probability. This work describes a system that reranks the top 10 most likely CRF candidate VMWE sequences using a decision tree regression model. The reranker aims to operationalize the intuition that a non-compositional MWE can have a different distributional behavior than that of its constituent words. This is why it uses semantic features based on comparing the context vector of a candidate expression against those of its constituent words. However, not all VMWE are non-compositional, and analysis shows that non-semantic features also play an important role in the behavior of the reranker. In fact, the analysis shows that the combination of the sequential approach of the CRF component with the context-based approach of the reranker is the main factor of improvement: our reranker achieves a 12% macro-average F1-score improvement on the basic CRF method, as measured using data from PARSEME shared task on VMWE identification.
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Keyword:
Algorithms; Artificial intelligence; Computational linguistics; Computer engineering; conditional random fields; Language; Linguistics; Machine learning; Multiword Expression; MWE identification; semantic reranking
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URL: http://doras.dcu.ie/24500/
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Semantic reranking of CRF label sequences for verbal multiword expression identification ; Multiword expressions at length and in depth: Extended papers from the MWE 2017 workshop
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Detecting sections and entities in court decisions using HMM and CRF graphical models
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In: Conférence Extraction et Gestion des Connaissances ; https://hal.archives-ouvertes.fr/hal-02101479 ; Conférence Extraction et Gestion des Connaissances, Université Grenoble alpes (UGA), Jan 2017, Grenoble, France ; http://egc2017.imag.fr/ (2017)
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Detection of Verbal Multi-Word Expressions via Conditional Random Fields with Syntactic Dependency Features and Semantic Re-Ranking
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In: Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017) ; https://hal.archives-ouvertes.fr/hal-01520762 ; Proceedings of the 13th Workshop on Multiword Expressions (MWE 2017), Apr 2017, Valencia, Spain. pp.114-120 ; http://multiword.sourceforge.net/ (2017)
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Detection of verbal multi-word expressions via conditional random fields with syntactic dependency features and semantic re-ranking
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In: Maldonado, Alfredo orcid:0000-0001-8426-5249 , Han, Lifeng orcid:0000-0002-3221-2185 , Moreau, Erwan orcid:0000-0001-7692-526X , Alsulaimani, Ashjan, Chowdhury, Koel, Vogel, Carl orcid:0000-0001-8928-8546 and Liu, Qun orcid:0000-0002-7000-1792 (2017) Detection of verbal multi-word expressions via conditional random fields with syntactic dependency features and semantic re-ranking. In: 13th Workshop on Multiword Expressions (MWE 2017), Apr 2017, Valencia, Spain. (2017)
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Strategies to select examples for Active Learning with Conditional Random Fields
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In: CICLing 2017 - 18th International Conference on Computational Linguistics and Intelligent Text Processing ; https://hal.archives-ouvertes.fr/hal-01621338 ; CICLing 2017 - 18th International Conference on Computational Linguistics and Intelligent Text Processing, Apr 2017, Budapest, Hungary. pp.1-14 (2017)
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Statistical Pronunciation Adaptation for Spontaneous Speech Synthesis
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In: Text, Speech and Dialogue (TSD) ; https://hal.inria.fr/hal-01532035 ; Text, Speech and Dialogue (TSD), Aug 2017, Prague, Czech Republic (2017)
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Structuration in named entities ; La structuration dans les entités nommées
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In: https://tel.archives-ouvertes.fr/tel-01772268 ; Linguistique. Université Sorbonne Paris Cité, 2017. Français. ⟨NNT : 2017USPCA100⟩ (2017)
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Context identification of sentences in related work sections using a conditional random field: towards intelligent digital libraries
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A 2D CRF Model for Sentence Alignment
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In: 9th Workshop on Building and Using Comparable Corpora ; https://hal.archives-ouvertes.fr/hal-01388656 ; 9th Workshop on Building and Using Comparable Corpora, 2016, Portorož, Slovenia ; http://lrec2016.lrec-conf.org/en/ (2016)
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A Hybrid Approach Using Maximum Entropy Model and Conditional Random Fields to Identify Tibetan Person Names
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In: Jia, Yangji; Li, Yachao; Zong, Chengqing; & Yu, Hongzhi. (2016). A Hybrid Approach Using Maximum Entropy Model and Conditional Random Fields to Identify Tibetan Person Names. Himalayan Linguistics, 15(1). doi:10.5070/H915130107. Retrieved from: http://www.escholarship.org/uc/item/8k20d3x6 (2016)
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Understanding Social Media Texts with Minimum Human Effort on #Twitter
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In: Language and the new (instant) media (PLIN) ; https://hal.archives-ouvertes.fr/hal-01490018 ; Language and the new (instant) media (PLIN), May 2016, Louvain-la-Neuve, Belgium (2016)
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Improving TTS with corpus-specific pronunciation adaptation
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In: Interspeech ; https://hal.inria.fr/hal-01338111 ; Interspeech, Sep 2016, San Francisco, United States (2016)
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Phonétisation statistique adaptable d'énoncés pour le français
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In: Journées d'Études sur la Parole ; https://hal.inria.fr/hal-01321358 ; Journées d'Études sur la Parole, Jul 2016, Paris, France (2016)
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МОРФОЛОГИЧЕСКИЙ И СИНТАКСИЧЕСКИЙ АНАЛИЗ ТЕКСТА НА ПЕРСИДСКОМ ЯЗЫКЕ С ПОМОЩЬЮ УСЛОВНЫХ СЛУЧАЙНЫХ ПОЛЕЙ ... : MORPHOLOGICAL AND SYNTACTIC ANALYSIS OF PERSIAN TEXT WITH CONDITIONAL RANDOM FIELDS ...
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