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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 – 9 of 9 1 Cognitive aspects of computational language acquisition Villavicencio, Aline [Herausgeber]; Poibeau, Thierry [Herausgeber]; Korhonen, Anna [Herausgeber]. - 2013 DNB Subject Category Language Show details 2 Cognitive Aspects of Computational Language Acquisition Villavicencio, Aline Herausgeber]. - Berlin, Heidelberg : Springer Berlin Heidelberg, 2013 DNB Subject Category Language Show details 3 Cognitive Aspects of Computational Language Acquisition Villavicencio, Aline; Poibeau, Thierry; Korhonen, Anna. - Berlin, Heidelberg : Springer Berlin Heidelberg, 2013 UB Frankfurt Linguistik Show details 4 Tools and procedures for the acquisition of morphological and syntactic information from corpora Korhonen, Anna In: Wörterbücher. Dictionaries. Dictionnaires: Ein internationales Handbuch zur Lexikographie. An International Encyclopedia of Lexicography. Encyclopédie international de lexicographie (HSK 5.4) (2013), 1405-1415 IDS OBELEX meta Show details 5 Cognitive Aspects of Computational Language Acquisition Villavicencio, Aline; Poibeau, Thierry; Korhonen, Anna. - : HAL CCSD, 2013. : Springer, 2013 In: https://hal.archives-ouvertes.fr/hal-00783282 ; Springer, pp.330, 2013, 978-3-642-31863-4 (2013) BASE Show details 6 A Tensor-based Factorization Model of Semantic Compositionality Van De Cruys, Tim; Poibeau, Thierry; Korhonen, Anna In: Proceedings of the Conference of the North American Chapter of the Association of Computational Linguistics (HTL-NAACL) ; Conference of the North American Chapter of the Association of Computational Linguistics (HTL-NAACL) ; https://hal.archives-ouvertes.fr/hal-00997334 ; Conference of the North American Chapter of the Association of Computational Linguistics (HTL-NAACL), Jun 2013, Atlanta, United States. pp.1142-1151 (2013) BASE Show details 7 Computational Modeling as a Methodology for Studying Human Language Learning Poibeau, Thierry; Villavicencio, Aline; Korhonen, Anna... In: Cognitive Aspects of Computational Language Acquisition ; https://hal.archives-ouvertes.fr/hal-00783285 ; A. Villavicencio, T. Poibeau, A. Korhonen and A. Alishahi. Cognitive Aspects of Computational Language Acquisition, Springer, pp.1-26, 2013, Theory and Applications of Natural Language Processing, 978-3-642-31863-4 (2013) BASE Show details 8 Active learning-based information structure analysis of full scientific articles and two applications for biomedical literature review Guo, Yufan; Silins, Ilona; Stenius, Ulla. - : Oxford University Press, 2013 BASE Show details 9 Automatic induction of verb classes using clustering Sun, Lin. - : University of Cambridge, 2013. : Faculty of Computer Science and Technology, 2013. : Computer Laboratory, 2013 Abstract: Verb classifications have attracted a great deal of interest in both linguistics and natural language processing (NLP). They have proved useful for important tasks and applications, including e.g. computational lexicography, parsing, word sense disambiguation, semantic role labelling, information extraction, question-answering, and machine translation (Swier and Stevenson, 2004; Dang, 2004; Shi and Mihalcea, 2005; Kipper et al., 2008; Zapirain et al., 2008; Rios et al., 2011). Particularly useful are classes which capture generalizations about a range of linguistic properties (e.g. lexical, (morpho-)syntactic, semantic), such as those proposed by Beth Levin (1993). However, full exploitation of such classes in real-world tasks has been limited because no comprehensive or domain-specific lexical classification is available. This thesis investigates how Levin-style lexical semantic classes could be learned automatically from corpus data. Automatic acquisition is cost-effective when it involves either no or minimal supervision and it can be applied to any domain of interest where adequate corpus data is available. We improve on earlier work on automatic verb clustering. We introduce new features and new clustering methods to improve the accuracy and coverage. We evaluate our methods and features on well-established cross-domain datasets in English, on a specific domain of English (the biomedical) and on another language (French), reporting promising results. Finally, our task-based evaluation demonstrates that the automatically acquired lexical classes enable new approaches to some NLP tasks (e.g. metaphor identification) and help to improve the accuracy of existing ones (e.g. argumentative zoning). ; This work was supported by a Dorothy Hodgkin PhD Scholarship. Keyword: Langauge acquisition; Lexical semantics; Unsupervised learning; Verb classification; Verb clustering URL: http://www.dspace.cam.ac.uk/handle/1810/244714 https://www.repository.cam.ac.uk/handle/1810/244714 https://doi.org/10.17863/CAM.16379 BASE Hide details

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