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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 Hits 1 – 10 of 10 1 English machine reading comprehension: new approaches to answering multiple-choice questions Dzendzik, Daria. - : Dublin City University. School of Computing, 2021. : Dublin City University. ADAPT, 2021 In: Dzendzik, Daria (2021) English machine reading comprehension: new approaches to answering multiple-choice questions. PhD thesis, Dublin City University. (2021) BASE Show details 2 Automatic processing of code-mixed social media content Barman, Utsab. - : Dublin City University. School of Computing, 2019. : Dublin City University. ADAPT, 2019 In: Barman, Utsab (2019) Automatic processing of code-mixed social media content. PhD thesis, Dublin City University. (2019) BASE Show details 3 Promoting user engagement and learning in search tasks by effective document representation Arora, Piyush. - : Dublin City University. School of Computing, 2018. : Dublin City University. ADAPT, 2018 In: Arora, Piyush orcid:0000-0002-4261-2860 (2018) Promoting user engagement and learning in search tasks by effective document representation. PhD thesis, Dublin City University. (2018) BASE Show details 4 Learning to represent, categorise and rank in community question answering Bogdanova, Daria. - : Dublin City University. School of Computing, 2018 In: Bogdanova, Daria (2018) Learning to represent, categorise and rank in community question answering. PhD thesis, Dublin City University. (2018) Abstract: The task of Question Answering (QA) is arguably one of the oldest tasks in Natural Language Processing, attracting high levels of interest from both industry and academia. However, most research has focused on factoid questions, e.g. Who is the president of Ireland? In contrast, research on answering non-factoid questions, such as manner, reason, difference and opinion questions, has been rather piecemeal. This was largely due to the absence of available labelled data for the task. This is changing, however, with the growing popularity of Community Question Answering (CQA) websites, such as Quora, Yahoo! Answers and the Stack Exchange family of forums. These websites provide natural labelled data allowing us to apply machine learning techniques. Most previous state-of-the-art approaches to the tasks of CQA-based question answering involved handcrafted features in combination with linear models. In this thesis we hypothesise that the use of handcrafted features can be avoided and the tasks can be approached with representation learning techniques, specifically deep learning. In the first part of this thesis we give an overview of deep learning in natural language processing and empirically evaluate our hypothesis on the task of detecting semantically equivalent questions, i.e. predicting if two questions can be answered by the same answer. In the second part of the thesis we address the task of answer ranking, i.e. determining how suitable an answer is for a given question. In order to determine the suitability of representation learning for the task of answer ranking, we provide a rigorous experimental evaluation of various neural architectures, based on feedforward, recurrent and convolutional neural networks, as well as their combinations. This thesis shows that deep learning is a very suitable approach to CQA-based QA, achieving state-of-the-art results on the two tasks we addressed. Keyword: Artificial intelligence; Computational linguistics; Machine learning URL: http://doras.dcu.ie/22121/ BASE Hide details 5 Report on ACL survey on preprint publishing and reviewing Foster, Jennifer; Nivre, Joakim; Zhao, Shiqi. - : Association for Computational Linguistics (ACL), 2017 In: Foster, Jennifer orcid:0000-0002-7789-4853 , Hearst, Marti, Nivre, Joakim orcid:0000-0002-7873-3971 and Zhao, Shiqi (2017) Report on ACL survey on preprint publishing and reviewing. Policy Report. Association for Computational Linguistics (ACL). (2017) BASE Show details 6 Irish dependency treebanking and parsing Lynn, Teresa. - : Dublin City University. School of Computing, 2016. : Dublin City University. ADAPT, 2016 In: Lynn, Teresa (2016) Irish dependency treebanking and parsing. PhD thesis, Dublin City University. (2016) BASE Show details 7 The role of syntax and semantics in machine translation and quality estimation of machine-translated user-generated content Zadeh Kaljahi, Rasoul Samad. - : Dublin City University. School of Computing, 2015. : Dublin City University. National Centre for Language Technology (NCLT), 2015. : Dublin City University. ADAPT, 2015 In: Zadeh Kaljahi, Rasoul Samad (2015) The role of syntax and semantics in machine translation and quality estimation of machine-translated user-generated content. PhD thesis, Dublin City University. (2015) BASE Show details 8 Detecting grammatical errors with treebank-induced, probabilistic parsers Wagner, Joachim. - : Dublin City University. School of Computing, 2012 In: Wagner, Joachim orcid:0000-0002-8290-3849 (2012) Detecting grammatical errors with treebank-induced, probabilistic parsers. PhD thesis, Dublin City University. (2012) BASE Show details 9 A case study of the process of formulating a strategic plan for the delivery of mental health services in an urban school district Foster, Jennifer. - 2010 BASE Show details 10 Good reasons for noting bad grammar : empirical investigations into the parsing of ungrammatical written English Foster, Jennifer. - : Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2005 BASE Show details

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