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An Enhanced Corpus for Arabic Newspapers Comments
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In: ISSN: 1683-3198 ; International Arab Journal of Information Technology ; https://hal.archives-ouvertes.fr/hal-03124728 ; International Arab Journal of Information Technology, Colleges of Computing and Information Society (CCIS), 2020, 17 (5), pp.789-798. ⟨10.34028/iajit/17/5/12⟩ (2020)
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Sonnet Combinatorics with OuPoCo
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In: 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature ; https://hal.archives-ouvertes.fr/hal-03084603 ; 4th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, ACL-SIGHUM, Dec 2020, Barcelona, Spain ; https://www.aclweb.org/anthology/volumes/2020.latechclfl-1/ (2020)
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Text Analytics ; Text Analytics: Advances and Challenges
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In: https://hal.archives-ouvertes.fr/hal-03099604 ; Springer, 2020, 978-3-030-52679-5 (2020)
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NTeALan Dictionaries Platforms: An Example Of Collaboration-Based Model
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In: Proceedings of the 1st International Workshop on Language Technology Platforms (IWLTP 2020) ; https://hal.archives-ouvertes.fr/hal-02701912 ; Proceedings of the 1st International Workshop on Language Technology Platforms (IWLTP 2020), 2020, pp.11 - 16 (2020)
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Factions: acts of worldbuilding on social media platforms ...
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Computational Propaganda: Targeted Advertising and the Perception of Truth
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In: Conference Papers (2020)
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Overcoming Alzheimer’s Disease Stigma by Leveraging Artificial Intelligence and Blockchain Technologies
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In: Brain Sciences ; Volume 10 ; Issue 3 (2020)
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Conversational Language Learning for Human-Robot Interaction
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USING DEEP LEARNING AND LINGUISTIC ANALYSIS TO PREDICT FAKE NEWS WITHIN TEXT
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In: Master's Projects (2020)
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Comparison of Word2vec with Hash2vec for Machine Translation
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In: Master's Projects (2020)
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LINGUISTIC AND HUMANITARIAN COMPETENCE OF FUTURE ENGINEERS: THE PHILOSOPHICAL AND ANTHROPOLOGICAL ASPECT
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In: Human Studies. Series of Pedagogy; № 10/42 (2020); 122-134 ; Людинознавчі студії. Серія Педагогіка; № 10/42 (2020); 122-134 ; 2413-2039 ; 2313-2094 (2020)
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Речевые маркеры обмана в устных ответах Джеймса Коми об использовании ФБР юридического инструмента FISA ; Verbal Markers of Deception in James Comey’s FISA Talk
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Кныш, А. Ю.. - : Издательство Уральского университета, 2020
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Digital Biomarkers for the Early Detection of Mild Cognitive Impairment: Artificial Intelligence Meets Virtual Reality
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Exploring Explicit and Implicit Feature Spaces in Natural Language Processing Using Self-Enrichment and Vector Space Analysis
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In: Electronic Thesis and Dissertation Repository (2020)
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Abstract:
Machine Learning in Natural Language Processing (NLP) deals directly with distributed representations of words and sentences. Words are transformed into vectors of real values, called embeddings, and used as the inputs to machine learning models. These architectures are then used to solve NLP tasks such as Sentiment Analysis and Natural Language Inference. While solving these tasks many models will create word embeddings and sentence embeddings as outputs. We are interested in how we can transform and analyze these output embeddings and modify our models, to both improve the task result and give us an understanding of the spaces. To this end we introduce the notion of explicit features, the actual values of the embeddings, and implicit features, information encoded into the space of vectors by solving the task, and hypothesis on an idealized spaces, where implicit features directly create the explicit features by means of basic linear algebra and set theory. To test if our output spaces are similar to our ideal space we vary the model and, motivated by Transformer architectures, introduce the notion of Self-Enriching layers. We also create idealized spaces, and run task experiments to see if the patterns of results can give us insight into the output spaces, as well we run transfer learning experiments to see what kinds of information are being represented by our models. Finally, we run direct analysis of the vectors of the word and sentence outputs for comparison.
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Keyword:
Artificial Intelligence and Robotics; distributed representations; natural language inference; natural language processing; sentence embeddings; sentiment analysis; word embeddings
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URL: https://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=9954&context=etd https://ir.lib.uwo.ca/etd/7471
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Human-AI Interaction in the Presence of Ambiguity: From Deliberation-based Labeling to Ambiguity-aware AI
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Cognitive discriminative feature selection using variance fractal dimension for the detection of cyber attacks
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Analogy between concepts
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In: ISSN: 0004-3702 ; Artificial Intelligence ; https://hal.inria.fr/hal-02186292 ; Artificial Intelligence, Elsevier, 2019, 275, pp.487-539. ⟨10.1016/j.artint.2019.06.008⟩ ; https://www.sciencedirect.com/science/article/pii/S0004370218301863 (2019)
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FEEL: a French Expanded Emotion Lexicon
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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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Εntity-level Εvent Ιmpact Αnalytics ; Analyse de l’Impact des Événements au Niveau des Entités
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In: https://hal.archives-ouvertes.fr/tel-02102795 ; Document and Text Processing. Normandie Université, Unicaen, EnsiCaen, CNRS, GREYC UMR 6072, 2019. English (2019)
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