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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 4 Hits 61 – 71 of 71 61 Morph-fitting: Fine-tuning word vector spaces with simple language-specific rules Vulic, Ivan; Mrkšic, N; Reichart, R. - : Association for Computational Linguistics, 2017. : ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers), 2017 BASE Show details 62 Automatic Selection of Context Configurations for Improved Class-Specific Word Representations Rappoport, Ari; Reichart, Roi; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2017. : https://arxiv.org/pdf/1608.05528.pdf, 2017. : Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017 BASE Show details 63 Evaluation by association: A systematic study of quantitative word association evaluation Vulić, I; Kiela, D; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2017. : 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference, 2017 BASE Show details 64 Initializing neural networks for hierarchical multi-label text classification Baker, Simon; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2017. : BioNLP 2017 - SIGBioMed Workshop on Biomedical Natural Language Processing, Proceedings of the 16th BioNLP Workshop, 2017 Abstract: Many tasks in the biomedical domain require the assignment of one or more predefined labels to input text, where the labels are a part of a hierarchical structure (such as a taxonomy). The conventional approach is to use a one-vs.-rest (OVR) classification setup, where a binary classifier is trained for each label in the taxonomy or ontology where all instances not belonging to the class are considered negative examples. The main drawbacks to this approach are that dependencies between classes are not leveraged in the training and classification process, and the additional computational cost of training parallel classifiers. In this paper, we apply a new method for hierarchical multi-label text classification that initializes a neural network model final hidden layer such that it leverages label co-occurrence relations such as hypernymy. This approach elegantly lends itself to hierarchical classifi- cation. We evaluated this approach using two hierarchical multi-label text classification tasks in the biomedical domain using both sentence- and document-level classi- fication. Our evaluation shows promising results for this approach. URL: https://doi.org/10.17863/CAM.12418 https://www.repository.cam.ac.uk/handle/1810/285913 BASE Hide details 65 On the role of seed lexicons in learning bilingual word embeddings ... Vulíc, I; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2016 BASE Show details 66 Is "universal syntax" universally useful for learning distributed word representations? ... Vulić, I; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2016 BASE Show details 67 On the role of seed lexicons in learning bilingual word embeddings Vulíc, I; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2016. : http://www.aclweb.org/anthology/P/P16/P16-1024.pdf, 2016. : 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers, 2016 BASE Show details 68 Anchoring and agreement in syntactic annotations Berzak, Y; Huang, Yan; Barbu, A. - : Association for Computational Linguistics, 2016. : http://dspace.mit.edu/bitstream/handle/1721.1/104453/CBMM-Memo-055.pdf?sequence=1, 2016. : EMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings, 2016 BASE Show details 69 Is "universal syntax" universally useful for learning distributed word representations? Vulić, I; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2016. : https://www.aclweb.org/anthology/P/P16/P16-2084.pdf, 2016. : 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Short Papers, 2016 BASE Show details 70 Unsupervised Declarative Knowledge Induction for Constraint-Based Learning of Information Structure in Scientific Documents Guo, Yufan; Reichart, Roi; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2015. : https://ie.technion.ac.il/%20roiri/papers/dec-knowledge-learning-tacl.pdf, 2015. : Transactions of Association for Computational Linguistics, 2015 BASE Show details 71 Exploring subdomain variation in biomedical language. Lippincott, Thomas; Séaghdha, Diarmuid Ó; Korhonen, Anna-Leena. - : Springer Science and Business Media LLC, 2011. : BMC Bioinformatics, 2011 BASE Show details Page: 1 2 3 4

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