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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 Hits 1 – 20 of 47 1 Deep learning approaches to text production Narayan, Shashi; Gardent, Claire. - [San Rafael, California] : Morgan & Claypool Publishers, 2020 Leibniz-Zentrum Allgemeine Sprachwissenschaft Show details 2 Hands-on natural language processing with PyTorch 1.x : build smart, AI-driven linguistic applications using deep learning and NLP techniques Dop, Thomas. - Mumbai : Packt, 2020 BLLDB UB Frankfurt Linguistik Show details 3 Le traitement automatique des langues en question : des machines qui comprennent le français ? Cori, Marcel. - [Paris] : Cassini, 2020 BLLDB UB Frankfurt Linguistik Show details 4 Natural language processing with Spark NLP : learning to understand text at scale Thomas, Alex. - Tokyo : O'Reilly, 2020 BLLDB UB Frankfurt Linguistik Show details 5 Languages in space and time : models and methods from complex systems theory Patriarca, Marco; Léonard, Jean-Léo; Heinsalu, Els. - Cambridge, United Kingdom : Cambridge University Press, 2020 BLLDB UB Frankfurt Linguistik Show details 6 Enriched meanings: natural language semantics with category theory Asudeh, Ash; Giorgolo, Gianluca. - London : Oxford University Press, 2020 IDS Bibliografie zur deutschen Grammatik Show details 7 Reflektierte alggorithmische Textanalyse: interdisziplinäre(s) Arbeiten in der CRETA-Werkstatt Reiter, Nils (Hrsg.); Pichler, Axel (Hrsg.); Kuhn, Jonas (Hrsg.). - Berlin; Boston, Mass. : de Gruyter, 2020 IDS Bibliografie zur deutschen Grammatik Show details 8 Machine translation of user-generated content Lohar, Pintu. - : Dublin City University. School of Computing, 2020. : Dublin City University. ADAPT, 2020 In: Lohar, Pintu (2020) Machine translation of user-generated content. PhD thesis, Dublin City University. (2020) Abstract: The world of social media has undergone huge evolution during the last few years. With the spread of social media and online forums, individual users actively participate in the generation of online content in different languages from all over the world. Sharing of online content has become much easier than before with the advent of popular websites such as Twitter, Facebook etc. Such content is referred to as ‘User-Generated Content’ (UGC). Some examples of UGC are user reviews, customer feedback, tweets etc. In general, UGC is informal and noisy in terms of linguistic norms. Such noise does not create significant problems for human to understand the content, but it can pose challenges for several natural language processing applications such as parsing, sentiment analysis, machine translation (MT), etc. An additional challenge for MT is sparseness of bilingual (translated) parallel UGC corpora. In this research, we explore the general issues in MT of UGC and set some research goals from our findings. One of our main goals is to exploit comparable corpora in order to extract parallel or semantically similar sentences. To accomplish this task, we design a document alignment system to extract semantically similar bilingual document pairs using the bilingual comparable corpora. We then apply strategies to extract parallel or semantically similar sentences from comparable corpora by transforming the document alignment system into a sentence alignment system. We seek to improve the quality of parallel data extraction for UGC translation and assemble the extracted data with the existing human translated resources. Another objective of this research is to demonstrate the usefulness of MT-based sentiment analysis. However, when using openly available systems such as Google Translate, the translation process may alter the sentiment in the target language. To cope with this phenomenon, we instead build fine-grained sentiment translation models that focus on sentiment preservation in the target language during translation. Keyword: Computational linguistics; Information retrieval; Machine learning; Machine translating; Translating and interpreting; User-Generated Content URL: http://doras.dcu.ie/24988/ BASE Hide details 9 Identifying and Modeling Code-Switched Language Soto Martinez, Victor. - 2020 BASE Show details 10 Essays on the use of computational linguistics in marketing Lemaire, Alain Philippe. - 2020 BASE Show details 11 Theoretical, empirical and computational approaches to agreement with coordination structures ; Les approches théoriques, empiriques et computationnelles pour l’accord avec les structures coordonnées An, Aixiu. - : HAL CCSD, 2020 In: https://tel.archives-ouvertes.fr/tel-03256559 ; Linguistics. Université de Paris, 2020. English. ⟨NNT : 2020UNIP7115⟩ (2020) BASE Show details 12 Machine learning methods for vector-based compositional semantics ... Maillard, Jean. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 13 Learning meaning representations for text generation with deep generative models ... Cao, Kris. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 14 Computer-Assisted Language Comparison in Practice. Tutorials on Computational Approaches to the History and Diversity of Languages. Volume II ... HC User. - : Humanities Commons, 2020 BASE Show details 15 Halbautomatisches Erstellen von Concept Maps : von Christoph Presch ... : Semi-automatic creation of concept maps ... Presch, Christoph. - : TU Wien, 2020 BASE Show details 16 Analyse einer dynamischen Sammlung von Zeitungsartikeln mit inhaltsbasierten Methoden ... : Analysis of a dynamic collection of news articles with content-based methods ... Neumeyer, Markus. - : TU Wien, 2020 BASE Show details 17 JOKE RECOMMENDER SYSTEM USING HUMOR THEORY ... Soumya Agrawal. - : Purdue University Graduate School, 2020 BASE Show details 18 JOKE RECOMMENDER SYSTEM USING HUMOR THEORY ... Soumya Agrawal. - : Purdue University Graduate School, 2020 BASE Show details 19 Identifying and Modeling Code-Switched Language ... Soto Martinez, Victor. - : Columbia University, 2020 BASE Show details 20 Essays on the use of computational linguistics in marketing ... Lemaire, Alain Philippe. - : Columbia University, 2020 BASE Show details Page: 1 2 3

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