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DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues
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In: Castilho, Sheila orcid:0000-0002-8416-6555 , Cavalheiro Camargo, João Lucas orcid:0000-0003-3746-1225 , Menezes, Miguel and Way, Andy orcid:0000-0001-5736-5930 (2021) DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues. In: Sixth Conference on Machine Translation (WMT21), 10-11 Nov 2021, Punta Cana, Dominican Republic (Online). ISBN 978-1-954085-94-7 (2021)
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Can Google Translate Rewire Your L2 English Processing?
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In: Resende, Natália orcid:0000-0002-5248-2457 and Way, Andy orcid:0000-0001-5736-5930 (2021) Can Google Translate Rewire Your L2 English Processing? Digital, 1 (1). pp. 66-85. ISSN 2673-6470 (2021)
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DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues ...
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Modelling source- and target-language syntactic Information as conditional context in interactive neural machine translation
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In: Gupta, Kamal Kumar, Haque, Rejwanul orcid:0000-0003-1680-0099 , Ekbal, Asif, Bhattacharyya, Pushpak and Way, Andy orcid:0000-0001-5736-5930 (2020) Modelling source- and target-language syntactic Information as conditional context in interactive neural machine translation. In: Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 2-6 Nov 2020, Lisboa, Portugal. (2020)
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Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation
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In: Soto, Xabier orcid:0000-0002-3622-6496 , Shterionov, Dimitar orcid:0000-0001-6300-797X , Poncelas, Alberto orcid:0000-0002-5089-1687 and Way, Andy orcid:0000-0001-5736-5930 (2020) Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation. In: Annual Conference of the Association for Computational Linguistics, ACL, 5-10 July 2020, Seattle, WA, USA (Online). (2020)
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MTrill project: machine translation impact on language learning
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In: Resende, Natália orcid:0000-0002-5248-2457 and Way, Andy orcid:0000-0001-5736-5930 (2020) MTrill project: machine translation impact on language learning. In: European Association for Machine Translation (EAMT) 2020, 3-5 Nov 2020, Lisbon, Portugal (Online). ISBN 978-989-33-0589-8 (2020)
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Syntax-informed interactive neural machine translation
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In: Gupta, Kamal Kumar, Haque, Rejwanul orcid:0000-0003-1680-0099 , Ekbal, Asif, Bhattacharyya, Pushpak and Way, Andy orcid:0000-0001-5736-5930 (2020) Syntax-informed interactive neural machine translation. In: The International Joint Conference on Neural Networks (IJCNN), 19-24 July 2020, Glasgow, UK (Online). (2020)
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MT syntactic priming effects on L2 English speakers
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In: Resende, Natália orcid:0000-0002-5248-2457 , Cowan, Benjamin orcid:0000-0002-8595-8132 and Way, Andy orcid:0000-0001-5736-5930 (2020) MT syntactic priming effects on L2 English speakers. In: European Association for Machine Translation (EAMT) 2020, 2-6 Nov 2010, Lisbon, Portugal (Online). ISBN 978-989-33-0589-8 (2020)
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Rapid development of competitive translation engines for access to multilingual COVID-19 information
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In: Way, Andy orcid:0000-0001-5736-5930 , Haque, Rejwanul orcid:0000-0003-1680-0099 , Xie, Guodong, Gaspari, Federico orcid:0000-0003-3808-8418 , Popović, Maja orcid:0000-0001-8234-8745 and Poncelas, Alberto orcid:0000-0002-5089-1687 (2020) Rapid development of competitive translation engines for access to multilingual COVID-19 information. Informatics . ISSN 2227-9709 (2020)
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Machine translation of user-generated content
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Lohar, Pintu. - : Dublin City University. School of Computing, 2020. : Dublin City University. ADAPT, 2020
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In: Lohar, Pintu (2020) Machine translation of user-generated content. PhD thesis, Dublin City University. (2020)
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Parallel data extraction using word embeddings
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In: Lohar, Pintu and Way, Andy orcid:0000-0001-5736-5930 (2020) Parallel data extraction using word embeddings. In: NLPTA 2020 : International Conference on NLP Techniques and Applications, 28-29 Nov 2020, London, UK (Online). (2020)
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The ADAPT’s submissions to the WMT20 biomedical translation task
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In: Nayak, Prashanth, Haque, Rejwanul orcid:0000-0003-1680-0099 and Way, Andy orcid:0000-0001-5736-5930 (2020) The ADAPT’s submissions to the WMT20 biomedical translation task. In: The Fifrth Conference on Machine Translation (The Biomedical Shared Task), 19-20 Nov 2020, Dominican Republic (Online). (In Press) (2020)
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Terminology-aware sentence mining for NMT domain adaptation: ADAPT’s submission to the Adap-MT 2020 English-to-Hindi AI translation shared task
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In: Haque, Rejwanul orcid:0000-0003-1680-0099 , Moslem, Yasmin orcid:0000-0003-4595-6877 and Way, Andy orcid:0000-0001-5736-5930 (2020) Terminology-aware sentence mining for NMT domain adaptation: ADAPT’s submission to the Adap-MT 2020 English-to-Hindi AI translation shared task. In: Workshop on Low Resource Domain Adaptation for Indic Machine Translation (Adap-MT 2020), 18-21 Dec 2020, Patna, India (Online). (2020)
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Investigating query expansion and coreference resolution in question answering on BERT
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In: Bhattacharjee, Santanu, Haque, Rejwanul orcid:0000-0003-1680-0099 , Maillette de Buy Wenniger, Gideon and Way, Andy orcid:0000-0001-5736-5930 (2020) Investigating query expansion and coreference resolution in question answering on BERT. In: 25th International Conference on Natural Language & Information Systems (NLDB 2020)), 24 - 26 June 2020, Saarbrücken, Germany (Online). ISBN 978-3-030-51309-2 (2020)
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Identifying complaints from product reviews: a case study on Hindi
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In: Singh, Raghvendra Pratap, Haque, Rejwanul orcid:0000-0003-1680-0099 , Hasanuzzaman, Mohammed orcid:0000-0003-1838-0091 and Way, Andy orcid:0000-0001-5736-5930 (2020) Identifying complaints from product reviews: a case study on Hindi. In: 28th Irish Conference on Artificial Intelligence and Cognitive Science, 7-8 Dec 2020, Dublin, Ireland. (2020)
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Abstract:
When an expectation does not meet reality in a real-world situation, the difference is usually expressed and communicated via an act which is complaint. Customers often post reviews on the products or services they purchase on the retailer websites and different social media platforms, and the reviews may reflect complaints about the products or services. Automatic recognition of customers’ complaints on products or services that they purchase can be crucial for the organizations, multinationals and online retailers since they can exploit this information to fulfil the customers’ expectations including managing and resolving the complaints. In this work, we present the supervised and semi-supervised learning strategies to identify users’ complaints from the language they use to post their reviews. In other words, we automatically identify complaints from the opinionated texts (reviews) about products posted in Hindi. For this, first we automatically crawled the Hindi reviews on different products from the the websites of the retail giant Amazon and the popular social media platform YouTube, and prepared a gold-standard data set via a systematic manual annotation process. We use state-of-the-art classification algorithms for the complaints identification task and our classification models achieve reasonable classification accuracy (F1 = 68.38%) on a gold-standard evaluation test set.
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Keyword:
Artificial intelligence; Computational linguistics; fastText;Dice coefficient; LSTM; Machine learning; Random walk; SMOTE
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URL: http://doras.dcu.ie/25290/
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The ADAPT Centre’s neural MT systems for the WAT 2020 document-level translation task
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In: Jooste, Wandri, Haque, Rejwanul orcid:0000-0003-1680-0099 and Way, Andy orcid:0000-0001-5736-5930 (2020) The ADAPT Centre’s neural MT systems for the WAT 2020 document-level translation task. In: 7th Workshop on Asian Translation (WAT2020), 4 Dec 2020, Suzhou, China (Online). (2020)
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Investigating low-resource machine translation for English-to-Tamil
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In: Ramesh, Akshai, Parthasarathy, Venkatesh Balavadhani, Haque, Rejwanul orcid:0000-0003-1680-0099 and Way, Andy orcid:0000-0001-5736-5930 (2020) Investigating low-resource machine translation for English-to-Tamil. In: Proceedings of the 3rd Workshop on Technologies for MT of Low Resource Languages (LoResMT 2020) AACL-IJCNLP, December 4-7, 2020, Suzhou, China (Online). (2020)
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The ADAPT system description for the STAPLE 2020 English-to-Portuguese translation task
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In: Haque, Rejwanul orcid:0000-0003-1680-0099 , Moslem, Yasmin and Way, Andy orcid:0000-0001-5736-5930 (2020) The ADAPT system description for the STAPLE 2020 English-to-Portuguese translation task. In: 4th Workshop on Neural Generation and Translation (WNGT 2020), 10 July 2020, Seattle, WA, USA (Online). (2020)
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