| Semeval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals I Hendrickx, SN Kim, Z Kozareva, P Nakov, DO Séaghdha, S Padó, ... Proceedings of the 5th International Workshop on Semantic Evaluation, 33-38, 2010 | 1170* | 2010 |
| Neural belief tracker: Data-driven dialogue state tracking N Mrkšić, DO Séaghdha, TH Wen, B Thomson, S Young arXiv preprint arXiv:1606.03777, 2016 | 567 | 2016 |
| Counter-fitting word vectors to linguistic constraints N Mrkšić, DO Séaghdha, B Thomson, M Gašić, L Rojas-Barahona, PH Su, ... arXiv preprint arXiv:1603.00892, 2016 | 526 | 2016 |
| Auralist: introducing serendipity into music recommendation YC Zhang, DÓ Séaghdha, D Quercia, T Jambor Proceedings of the fifth ACM international conference on Web search and data …, 2012 | 487 | 2012 |
| Semantic specialization of distributional word vector spaces using monolingual and cross-lingual constraints N Mrkšić, I Vulić, DÓ Séaghdha, I Leviant, R Reichart, M Gašić, ... Transactions of the association for Computational Linguistics 5, 309-324, 2017 | 250 | 2017 |
| Multi-domain dialog state tracking using recurrent neural networks N Mrkšić, DO Séaghdha, B Thomson, M Gašić, PH Su, D Vandyke, ... arXiv preprint arXiv:1506.07190, 2015 | 224 | 2015 |
| Optimizing dialogue policy decisions for digital assistants using implicit feedback B Thomson, DJ Vandyke, G Frazzingaro, SF DELGADO, TB Gunter, ... US Patent 10,810,274, 2020 | 183 | 2020 |
| Hierarchical belief states for digital assistants B Thomson, A Johannsen, DÓ Séaghdha, F Flego, L Simonelli, SJ Young, ... US Patent 10,482,874, 2019 | 176 | 2019 |
| Latent variable models of selectional preference DO Séaghdha Proceedings of the 48th Annual Meeting of the Association for Computational …, 2010 | 143 | 2010 |
| Text mining for literature review and knowledge discovery in cancer risk assessment and research A Korhonen, D Ó Séaghdha, I Silins, L Sun, J Högberg, U Stenius PloS one 7 (4), e33427, 2012 | 84 | 2012 |
| SemEval-2010 task 9: The interpretation of noun compounds using paraphrasing verbs and prepositions C Butnariu, SN Kim, P Nakov, DO Séaghdha, S Szpakowicz, T Veale Proceedings of the 5th International Workshop on Semantic Evaluation, 39-44, 2010 | 80 | 2010 |
| Predicting the impact of scientific concepts using full‐text features K McKeown, H Daume III, S Chaturvedi, J Paparrizos, K Thadani, P Barrio, ... Journal of the Association for Information Science and Technology 67 (11 …, 2016 | 79 | 2016 |
| SemEval-2013 task 4: Free paraphrases of noun compounds I Hendrickx, P Nakov, S Szpakowicz, Z Kozareva, DO Séaghdha, T Veale arXiv preprint arXiv:1911.10421, 2019 | 72 | 2019 |
| Semantic relations between nominals V Nastase, S Szpakowicz, P Nakov, DÓ Séagdha Springer Nature, 2022 | 63 | 2022 |
| Conversational semantic parsing for dialog state tracking J Cheng, D Agrawal, HM Alonso, S Bhargava, J Driesen, F Flego, ... arXiv preprint arXiv:2010.12770, 2020 | 57 | 2020 |
| Talk of the city: Our tweets, our community happiness D Quercia, DÒ Séaghdha, J Crowcroft Proceedings of the International AAAI Conference on Web and Social Media 6 …, 2012 | 56 | 2012 |
| Semantic classification with distributional kernels D Ó Séaghdha, A Copestake Proceedings of the 22nd International Conference on Computational …, 2008 | 56 | 2008 |
| Learning compound noun semantics DO Séaghdha University of Cambridge, Cambridge, UK, 2008 | 55 | 2008 |
| Emoticons and phrases: Status symbols in social media S Tchokni, DO Séaghdha, D Quercia Proceedings of the International AAAI Conference on Web and Social Media 8 …, 2014 | 54 | 2014 |
| Morph-fitting: Fine-tuning word vector spaces with simple language-specific rules I Vulić, N Mrkšić, R Reichart, DÓ Séaghdha, S Young, A Korhonen arXiv preprint arXiv:1706.00377, 2017 | 52 | 2017 |
Preslav NakovMBZUAIE-mailová adresa ověřena na: mbzuai.ac.ae
