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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5 6 7 8 9...13 Hits 81 – 100 of 249 81 Navegación de corpus a través de anotaciones lingüísticas automáticas obtenidas por Procesamiento del Lenguaje Natural: de anecdótico a ecdótico Ruiz Fabo, Pablo; Bermúdez Sabel, Helena In: Revista de Humanidades Digitales, vol. 4, pp. 136 (2019) BASE Show details 82 Identifying Semantic Divergences Across Languages Vyas, Yogarshi. - 2019 BASE Show details 83 A Combined CNN and LSTM Model for Arabic Sentiment Analysis Alayba, Abdulaziz,; Palade, Vasile; England, Matthew; Iqbal, Rahat In: Lecture Notes in Computer Science ; 2nd International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE) ; https://hal.inria.fr/hal-02060041 ; 2nd International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE), Aug 2018, Hamburg, Germany. pp.179-191, ⟨10.1007/978-3-319-99740-7_12⟩ (2018) Abstract: Part 2: MAKE-Text ; International audience ; Deep neural networks have shown good data modelling capabilities when dealing with challenging and large datasets from a wide range of application areas. Convolutional Neural Networks (CNNs) offer advantages in selecting good features and Long Short-Term Memory (LSTM) networks have proven good abilities of learning sequential data. Both approaches have been reported to provide improved results in areas such image processing, voice recognition, language translation and other Natural Language Processing (NLP) tasks. Sentiment classification for short text messages from Twitter is a challenging task, and the complexity increases for Arabic language sentiment classification tasks because Arabic is a rich language in morphology. In addition, the availability of accurate pre-processing tools for Arabic is another current limitation, along with limited research available in this area. In this paper, we investigate the benefits of integrating CNNs and LSTMs and report obtained improved accuracy for Arabic sentiment analysis on different datasets. Additionally, we seek to consider the morphological diversity of particular Arabic words by using different sentiment classification levels. Keyword: [INFO]Computer Science [cs]; [SHS.INFO]Humanities and Social Sciences/Library and information sciences; Arabic sentiment classification; CNN; LSTM; Natural Language Processing(NLP) URL: https://hal.inria.fr/hal-02060041 https://doi.org/10.1007/978-3-319-99740-7_12 https://hal.inria.fr/hal-02060041/document https://hal.inria.fr/hal-02060041/file/472936_1_En_12_Chapter.pdf BASE Hide details 84 Dialog Acts Annotations for Online Chats ; Annotation en Actes de Dialogue pour les Conversations d’Assistance en Ligne Perrotin, Robin; Nasr, Alexis; Auguste, Jeremy 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) BASE Show details 85 Experimental IR Meets Multilinguality, Multimodality, and Interaction (CLEF 2018, Avignon,France) Bellot, Patrice; Trabelsi, Chiraz; Mothe, Josiane. - : HAL CCSD, 2018. : Springer Berlin / Heidelberg, 2018. : Springer, 2018 In: ISSN: 0302-9743 ; Lecture Notes in Computer Science ; 9th International Conference of the CLEF Association (CLEF 2018) ; https://hal.archives-ouvertes.fr/hal-03044243 ; Bellot, Patrice; Trabelsi, Chiraz; Mothe, Josiane; Murtagh, Fionn; Nie, Jian-Yun; Soulier, Laure; Sanjuan, Eric; Cappellato, Linda; Ferro, Nicola. 9th International Conference of the CLEF Association (CLEF 2018), Sep 2018, Avignon, France. Lecture Notes in Computer Science, Springer Berlin / Heidelberg; Springer, 2018, Experimental IR Meets Multilinguality, Multimodality, and Interaction, 978-3-319-98931-0. ⟨10.1007/978-3-319-98932-7⟩ ; https://link.springer.com/book/10.1007%2F978-3-319-98932-7 (2018) BASE Show details 86 From Emoji Usage to Categorical Emoji Prediction Guibon, Gaël; Ochs, Magalie; Bellot, Patrice In: 19th International Conference on Computational Linguistics and Intelligent Text Processing (CICLING 2018) ; https://hal-amu.archives-ouvertes.fr/hal-01871045 ; 19th International Conference on Computational Linguistics and Intelligent Text Processing (CICLING 2018), Mar 2018, Hanoï, Vietnam ; https://www.cicling.org/2018/ (2018) BASE Show details 87 CorpusExplorer Rüdiger, Jan Oliver. - : Jan Oliver Rüdiger, 2018 BASE Show details 88 Prediction of Psychosis Using Big Web Data in the United States Tadisetty, Srikanth In: http://rave.ohiolink.edu/etdc/view?acc_num=kent1532962079970169 (2018) BASE Show details 89 An Empirical Study of Word Embedding Dimensionality Reduction ... Ji, Yichao. - : Zenodo, 2018 BASE Show details 90 An Empirical Study of Word Embedding Dimensionality Reduction ... Ji, Yichao. - : Zenodo, 2018 BASE Show details 91 Chromium Conversations ... Meyers, Benjamin S.; Munaiah, Nuthan; Prud'hommeaux, Emily. - : Zenodo, 2018 BASE Show details 92 Chromium Conversations ... Meyers, Benjamin S.; Munaiah, Nuthan; Prud'hommeaux, Emily. - : Zenodo, 2018 BASE Show details 93 Data-Driven Language Understanding for Spoken Dialogue Systems ... Mrkšić, Nikola. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 94 ОБЛАЧНЫЕ СЕРВИСЫ ДЛЯ ОБРАБОТКИ ТЕКСТОВ НА ЕСТЕСТВЕННОМ ЯЗЫКЕ ... : CLOUD SERVICES FOR NATURAL LANGUAGE PROCESSING ... Mukhamediev, R.I.; Symagulov, A.; Kuchin, Y.I.. - : Международный научный журнал “Современные информационные технологии и ИТ-образование”, 2018 BASE Show details 95 Training Neural Models for Abstractive Text Summarization Kryściński, Wojciech. - : KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018 BASE Show details 96 Automatic Annotation And Retrieval System (Ilars) For Enhancing Organizational E-Learning ... Chuan-Jun Su*, Yin-An Chen. - : Zenodo, 2018 BASE Show details 97 Automatic Annotation And Retrieval System (Ilars) For Enhancing Organizational E-Learning ... Chuan-Jun Su*, Yin-An Chen. - : Zenodo, 2018 BASE Show details 98 Proposition-based summarization with a coherence-driven incremental model Fang, Yimai. - : University of Cambridge, 2018. : Computer Science and Technology, 2018. : Hughes Hall, 2018 BASE Show details 99 NLP Corpus Observatory – Looking for Constellations in Parallel Corpora to Improve Learners’ Collocational Skills Schneider, Gerold; Graën, Johannes In: Schneider, Gerold; Graën, Johannes (2018). NLP Corpus Observatory – Looking for Constellations in Parallel Corpora to Improve Learners’ Collocational Skills. In: 7th Workshop on NLP for Computer Assisted Language Learning at SLTC 2018 (NLP4CALL 2018), Stockholm, 7 November 2018 - 7 November 2018, 69-78. (2018) BASE Show details 100 Simple Convolutional Neural Networks with Linguistically-Annotated Input for Answer Selection in Question Answering Sequiera, Royal. - : University of Waterloo, 2018 BASE Show details Page: 1 2 3 4 5 6 7 8 9...13

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