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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 Hits 1 – 20 of 55 1 Semantic Data Set Construction from Human Clustering and Spatial Arrangement ... Majewska, Olga; McCarthy, Diana; Van Den Bosch, Jasper JF. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 2 Context vs Target Word: Quantifying Biases in Lexical Semantic Datasets ... Liu, Qianchu; McCarthy, Diana; Korhonen, Anna. - : arXiv, 2021 BASE Show details 3 AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ... Liu, Qianchu; Ponti, Edoardo M.; McCarthy, Diana. - : arXiv, 2021 BASE Show details 4 AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Korhonen, Anna; Liu, Qianchu. - : Underline Science Inc., 2021 BASE Show details 5 Quantifying lexical usage: vocabulary pertaining to ecosystems and the environment Burgess, Jacquelin; Wild, Kate; McCarthy, Diana. - : Edinburgh University Press, 2021 BASE Show details 6 Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ... Majewska, Olga; Vulic, Ivan; McCarthy, Diana. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 7 Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ... The 28th International Conference on Computational Linguistics 2020; Korhonen, Anna; Majewska, Olga. - : Underline Science Inc., 2020 BASE Show details 8 Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis Majewska, Olga; Vulic, Ivan; McCarthy, Diana. - : International Committee on Computational Linguistics, 2020. : https://www.aclweb.org/anthology/2020.coling-main.423, 2020. : Proceedings of the 28th International Conference on Computational Linguistics (COLING 2020), 2020 BASE Show details 9 Investigating the cross-lingual translatability of VerbNet-style classification. ... Majewska, Olga; Vulić, Ivan; McCarthy, Diana. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 10 Investigating the cross-lingual translatability of VerbNet-style classification. Majewska, Olga; Vulić, Ivan; McCarthy, Diana. - : Springer Science and Business Media LLC, 2018. : Lang Resour Eval, 2018 BASE Show details 11 Licensing Complex Prepositions via Lexical Constraints Trawiński, Beata [Verfasser]; Bond, Francis [Herausgeber]; Korhonen, Anna [Herausgeber]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017 DNB Subject Category Language Show details 12 Investigating the cross-lingual translatability of VerbNet-style classification [<Journal>] Majewska, Olga [Verfasser]; Vulić, Ivan [Sonstige]; McCarthy, Diana [Sonstige]. DNB Subject Category Language Show details 13 Word Sense Clustering and Clusterability McCarthy, Diana; Apidianaki, Marianna; Erk, Katrin In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01838502 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2016, 42, pp.245-275. &#x27E8;10.1162/COLI&#x27E9; (2016) Abstract: International audience ; Word sense disambiguation and the related field of automated word sense induction traditionally assume that the occurrences of a lemma can be partitioned into senses. But this seems to be a much easier task for some lemmas than others. Our work builds on recent work that proposes describing word meaning in a graded fashion rather than through a strict partition into senses; in this article we argue that not all lemmas may need the more complex graded analysis, depending on their partitionability. Although there is plenty of evidence from previous studies and from the linguistics literature that there is a spectrum of partitionability of word meanings, this is the first attempt to measure the phenomenon and to couple the machine learning literature on clusterability with word usage data used in computational linguistics.We propose to operationalize partitionability as clusterability, a measure of how easy the occurrences of a lemma are to cluster. We test two ways of measuring clusterability: (1) existing measures from the machine learning literature that aim to measure the goodness of optimal k-means clusterings, and (2) the idea that if a lemma is more clusterable, two clusterings based on two different “views” of the same data points will be more congruent. The two views that we use are two different sets of manually constructed lexical substitutes for the target lemma, on the one hand monolingual paraphrases, and on the other hand translations. We apply automatic clustering to the manual annotations. We use manual annotations because we want the representations of the instances that we cluster to be as informative and “clean” as possible. We show that when we control for polysemy, our measures of clusterability tend to correlate with partitionability, in particular some of the type-(1) clusterability measures, and that these measures outperform a baseline that relies on the amount of overlap in a soft clustering. Keyword: [INFO]Computer Science [cs]; clusterability; word sense clustering URL: https://hal.archives-ouvertes.fr/hal-01838502 https://doi.org/10.1162/COLI https://hal.archives-ouvertes.fr/hal-01838502/document https://hal.archives-ouvertes.fr/hal-01838502/file/COLI_a_00247.pdf BASE Hide details 14 Integrating character representations into Chinese word embedding Chen, Xingyuan; Jin, Peng; McCarthy, Diana Frances. - : Springer International Publishing, 2016 BASE Show details 15 Inferences during reading Ratcliff, Roger; Broek, Paul van den; Cain, Kate. - Cambridge : Cambridge University Press, 2015 BLLDB UB Frankfurt Linguistik Show details 16 Semantic clustering of pivot paraphrases Apidianaki, Marianna; Verzeni, Emilia; McCarthy, Diana In: International Conference on Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-01838559 ; International Conference on Language Resources and Evaluation, Jan 2014, Reykjavik, Iceland (2014) BASE Show details 17 A lexicographic appraisal of an automatic approach for detecting new wordsenses Cook, Paul; Lau, Jey H.; Rundell, Michael... In: Electronic lexicography in the 21st century: thinking outside the paper. Proceedings of the eLex 2013 conference, 17 - 19 October 2013, Tallinn, Estonia (2013), 49-65 IDS OBELEX meta Show details 18 Quantifying lexical usage: vocabulary pertaining to ecosystems and the environment Wild, Kate; Burgess, Jacquelin; Church, Andrew... In: Corpora. - Edinburgh : Univ. Press 8 (2013) 1, 53-79 BLLDB OLC Linguistik Show details 19 Quantifying lexical usage: vocabulary pertaining to ecosystems and the environment Church, Andrew; McCarthy, Diana; Wild, Kate. - : Edinburgh University Press, 2013 BASE Show details 20 Finding Meaning in Context Using Graph Algorithms in Mono- and Cross-lingual Settings Sinha, Ravi Som. - : University of North Texas, 2013 BASE Show details Page: 1 2 3

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