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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 45 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) Abstract: Reading comprehension is often tested by measuring a person or system’s ability to answer questions about a given text. Machine reading comprehension datasets have proliferated in recent years, particularly for the English language. The aim of this thesis is to investigate and improve data-driven approaches to automatic reading comprehension. Firstly, I provide a full classification of question and answer types for the reading comprehension task. I also present a systematic overview of English reading comprehension datasets (over 50 datasets). I observe that the majority of questions were created using crowdsourcing and the most popular data source is Wikipedia. There is also a lack of why, when, and where questions. Additionally, I address the question “What makes a dataset difficult?” and highlight the difference between datasets created for people and datasets created for machine reading comprehension. Secondly, focusing on multiple-choice question answering, I propose a computationally light method for answer selection based on string similarities and logistic regression. At the time (December 2017), the proposed approach showed the best performance on two datasets (MovieQA and MCQA: IJCNLP 2017 Shared Task 5 Multi-choice Question Answering in Examinations) outperforming some CNN-based methods. Thirdly, I investigate methods for Boolean Reading Comprehension tasks including the use of Knowledge Graph (KG) information for answering questions. I provide an error analysis of a transformer model’s performance on the BoolQ dataset. This reveals several important issues such as unstable model behaviour and some issues with the dataset itself. Experiments with incorporating knowledge graph information into a baseline transformer model do not show a clear improvement due to a combination of the model’s ability to capture new information, inaccuracies in the knowledge graph, and imprecision in entity linking. Finally, I develop a Boolean Reading Comprehension dataset based on spontaneously user-generated questions and reviews which is extremely close to a real-life question-answering scenario. I provide a classification of question difficulty and establish a transformer-based baseline for the new proposed dataset. Keyword: Artificial intelligence; Computational linguistics; Information retrieval; Machine learning; machine reading comprehension; question answering; transformer language models URL: http://doras.dcu.ie/26534/ BASE Hide details 2 The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Barry, James; Foster, Jennifer. - : Underline Science Inc., 2021 BASE Show details 3 Revisiting Tri-training of Dependency Parsers ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Foster, Jennifer; Wagner, Joachim. - : Underline Science Inc., 2021 BASE Show details 4 English Machine Reading Comprehension Datasets: A Survey ; Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing Vogel, Carl; Foster, Jennifer; Dzendzik, Daria. - : Association for Computational Linguistics, 2021 BASE Show details 5 Annotating verbal MWEs in Irish for the PARSEME Shared Task 1.2 Lynn, Teresa; Foster, Jennifer; Walsh, Abigail In: Walsh, Abigail, Lynn, Teresa and Foster, Jennifer orcid:0000-0002-7789-4853 (2020) Annotating verbal MWEs in Irish for the PARSEME Shared Task 1.2. In: Joint Workshop on Multiword Expressions and Electronic Lexicons, 13 Dec 2020, Barcelona, Spain (Online). (2020) BASE Show details 6 Improving document-level sentiment analysis with user and product context Foster, Jennifer; Lyu, Chenyang; Graham, Yvette In: Lyu, Chenyang, Foster, Jennifer orcid:0000-0002-7789-4853 and Graham, Yvette (2020) Improving document-level sentiment analysis with user and product context. In: Proceedings of the 28th International Conference on Computational Linguistics, 8-13 Dec 20, Barcelona, Spain (Online). (2020) BASE Show details 7 How to make neural natural language generation as reliable as templates in task-oriented dialogue O'Connor, Alexander; Elder, Henry; Foster, Jennifer In: Elder, Henry, O'Connor, Alexander orcid:0000-0003-0301-999X and Foster, Jennifer orcid:0000-0002-7789-4853 (2020) How to make neural natural language generation as reliable as templates in task-oriented dialogue. In: 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 16-20 Nov 2020, Online. (2020) BASE Show details 8 Treebank embedding vectors for out-of-domain dependency parsing Wagner, Joachim; Barry, James; Foster, Jennifer In: Wagner, Joachim orcid:0000-0002-8290-3849 , Barry, James orcid:0000-0003-3051-585X and Foster, Jennifer orcid:0000-0002-7789-4853 (2020) Treebank embedding vectors for out-of-domain dependency parsing. In: 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), 05-10 Jul 2020, Online (virtual conference). (2020) BASE Show details 9 Q. Can knowledge graphs be used to answer Boolean questions? A. It’s complicated! Vogel, Carl; Dzendzik, Daria; Foster, Jennifer In: Dzendzik, Daria, Vogel, Carl orcid:0000-0001-8928-8546 and Foster, Jennifer orcid:0000-0002-7789-4853 (2020) Q. Can knowledge graphs be used to answer Boolean questions? A. It’s complicated! In: First Workshop on Insights from Negative Results in NLP, 10 Nov 2020, Online. (2020) BASE Show details 10 Cross-lingual parsing with polyglot training and multi-treebank learning: a Faroese case study Barry, James; Wagner, Joachim; Foster, Jennifer In: Barry, James orcid:0000-0003-3051-585X , Wagner, Joachim orcid:0000-0002-8290-3849 and Foster, Jennifer orcid:0000-0002-7789-4853 (2019) Cross-lingual parsing with polyglot training and multi-treebank learning: a Faroese case study. In: The 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019), 3 - 5 Nov 2019, Hong Kong, China. ISBN 978-1-950737-78-9 (2019) BASE Show details 11 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 12 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 13 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) BASE Show details 14 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 15 This is how we do it: Answer reranking for open-domain how questions with paragraph vectors and minimal feature engineering Foster, Jennifer; Bogdanova, Dasha In: Bogdanova, Dasha and Foster, Jennifer orcid:0000-0002-7789-4853 (2016) This is how we do it: Answer reranking for open-domain how questions with paragraph vectors and minimal feature engineering. In: The 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL 16), 12-17 Jun 2016, San Diego, CA. (2016) BASE Show details 16 DCU-ADAPT: Learning edit operations for microblog normalisation with the generalised perceptron Wagner, Joachim; Foster, Jennifer In: Wagner, Joachim orcid:0000-0002-8290-3849 and Foster, Jennifer orcid:0000-0002-7789-4853 (2015) DCU-ADAPT: Learning edit operations for microblog normalisation with the generalised perceptron. In: ACL 2015 Workshop on Noisy User-generated Text (W-NUT), 31 July 2015, Beijing, China. (2015) BASE Show details 17 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 18 DCU: using distributional semantics and domain adaptation for the semantic textual similarity SemEval-2015 Task 2 Foster, Jennifer; Hokamp, Chris; Jones, Gareth J.F.... In: Arora, Piyush orcid:0000-0002-4261-2860 , Hokamp, Chris orcid:0000-0002-7850-9398 , Foster, Jennifer orcid:0000-0002-7789-4853 and Jones, Gareth J.F. orcid:0000-0003-2923-8365 (2015) DCU: using distributional semantics and domain adaptation for the semantic textual similarity SemEval-2015 Task 2. In: International Workshop on Semantic Evaluation (SemEval 2015), 4-5 June 2015, Denver, Co. USA. (2015) BASE Show details 19 Code mixing: a challenge for language identification in the language of social media Barman, Utsab; Das, Amitava; Wagner, Joachim... In: Barman, Utsab, Das, Amitava orcid:0000-0003-3418-463X , Wagner, Joachim orcid:0000-0002-8290-3849 and Foster, Jennifer orcid:0000-0002-7789-4853 (2014) Code mixing: a challenge for language identification in the language of social media. In: First Workshop on Computational Approaches to Code Switching, 25 Oct 2014, Doha, Qatar. (2014) BASE Show details 20 DCU: aspect-based polarity classification for SemEval task 4 Wagner, Joachim; Foster, Jennifer; Arora, Piyush... In: Wagner, Joachim orcid:0000-0002-8290-3849 , Arora, Piyush orcid:0000-0002-4261-2860 , Cortes, Santiago, Barman, Utsab, Bogdanova, Dasha, Foster, Jennifer orcid:0000-0002-7789-4853 and Tounsi, Lamia (2014) DCU: aspect-based polarity classification for SemEval task 4. In: International Workshop on Semantic Evaluation (SemEval-2014), 23-24 Aug 2014, Dublin, Ireland. ISBN 978-1-941643-24-2 (2014) BASE Show details Page: 1 2 3

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