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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 – 2 of 2 1 Learning to Understand Phrases by Embedding the Dictionary ... Hill, Felix; Cho, Kyunghyun; Korhonen, Anna. - : arXiv, 2015 BASE Show details 2 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 Abstract: Inferring the information structure of scientific documents is useful for many NLP applications. Existing approaches to this task require substantial human effort. We propose a framework for constraint learning that reduces human involvement considerably. Our model uses topic models to identify latent topics and their key linguistic features in input documents, induces constraints from this information and maps sentences to their dominant information structure categories through a constrained unsupervised model. When the induced constraints are combined with a fully unsupervised model, the resulting model challenges existing lightly supervised featurebased models as well as unsupervised models that use manually constructed declarative knowledge. Our results demonstrate that useful declarative knowledge can be learned from data with very limited human involvement. ; This is the final published version. It first appeared at https://tacl2013.cs.columbia.edu/ojs/index.php/tacl/article/view/472. URL: https://www.repository.cam.ac.uk/handle/1810/247825 BASE Hide details

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