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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... 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) BASE Show 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 Abstract: With the advent of deep learning methods, researchers have been increasingly preferring deep learning methods over decades-old feature-engineering-inspired work in Natural Language Processing (NLP). The research community has been moving away from otherwise dominant feature engineering approaches; rather, is gravitating towards more complicated neural architectures. Highly competitive tools like part-of-speech taggers that exhibit human-like accuracy are traded off for complex networks, with the hope that the neural network will learn the features needed. In fact, there have been efforts to do NLP "from scratch" with neural networks that altogether eschew featuring engineering based tools (Collobert et al, 2011). In our research, we modify the input that is fed to neural networks by annotating the input with linguistic information: POS tags, Named Entity Recognition output, linguistic relations, etc. With just the addition of these linguistic features on a simple Siamese convolutional neural network, we are able to achieve state-of-the-art results. We argue that this strikes a better balance between feature vs. network engineering. Keyword: Answer selection; CNN; Feature engineering; Natural Language Processing; neural networks; NLP; Question Answering URL: http://hdl.handle.net/10012/13570 BASE Hide details Page: 1 2 3 4 5 6 7 8 9...13

Mobile view All Catalogues UB Frankfurt Linguistik 0 IDS Mannheim 0 OLC Linguistik 0 UB Frankfurt Retrokatalog 0 DNB Subject Category Language 0 Institut für Empirische Sprachwissenschaft 0 Leibniz-Centre General Linguistics (ZAS) 0 Bibliographies BLLDB 0 BDSL 0 IDS Bibliografie zur deutschen Grammatik 0 IDS Bibliografie zur Gesprächsforschung 0 IDS Konnektoren im Deutschen 0 IDS Präpositionen im Deutschen 0 IDS OBELEX meta 0 MPI-SHH Linguistics Collection 0 MPI for Psycholinguistics 0 Linked Open Data catalogues Annohub 0 Online resources Link directory 0 Journal directory 0 Database directory 0 Dictionary directory 0 Open access documents BASE 249 Linguistik-Repository 0 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0