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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 Hits 21 – 31 of 31 21 Verblexpor: A lexical resource with semantic roles for Portuguese Villavicencio, A.; Finatto, M.J.B.; Zilio, L.. - : European Language Resources Association (ELRA), 2016 BASE Show details 22 Filtering and measuring the intrinsic quality of human compositionality judgments Ramisch, C.; Cordeiro, S.; Villavicencio, A.. - : Association for Computational Linguistics, 2016 BASE Show details 23 Multiword expressions in child language Wilkens, R.; Idiart, M.; Villavicencio, A.. - : European Language Resources Association (ELRA), 2016 BASE Show details 24 mwetoolkit+sem: Integrating word embeddings in the mwetoolkit for semantic MWE processing Cordeiro, S.; Ramisch, C.; Villavicencio, A.. - : European Language Resources Association (ELRA), 2016 Abstract: This paper presents mwetoolkit+sem: an extension of the mwetoolkit that estimates semantic compositionality scores for multiword expressions (MWEs) based on word embeddings. First, we describe our implementation of vector-space operations working on distributional vectors. The compositionality score is based on the cosine distance between the MWE vector and the composition of the vectors of its member words. Our generic system can handle several types of word embeddings and MWE lists, and may combine individual word representations using several composition techniques. We evaluate our implementation on a dataset of 1042 English noun compounds (Farahmand et al., 2015), comparing different configurations of the underlying word embeddings and word-composition models. We show that our vector-based scores model non-compositionality better than standard association measures such as log-likelihood. URL: http://eprints.whiterose.ac.uk/153563/ https://www.aclweb.org/anthology/L16-1194 BASE Hide details 25 B2SG: a TOEFL-like task for Portuguese Wilkens, R.; Zilio, L.; Ferreira, E.. - : European Language Resources Association (ELRA), 2016 BASE Show details 26 Predicting the compositionality of nominal compounds: Giving word embeddings a hard time Cordeiro, S.; Ramisch, C.; Idiart, M.. - : Association for Computational Linguistics, 2016 BASE Show details 27 Matrix factorization using window sampling and negative sampling for improved word representations Salle, A.; Idiart, M.; Villavicencio, A.. - : Association for Computational Linguistics, 2016 BASE Show details 28 Estratégias de evocação lexical com critério semântico em adultos após acidente vascular cerebral no hemisfério direito / Semantic verbal fluency strategies in patients after a right-hemisphere stroke Becker, N.; Müller, J.D.L.; Rodrigues, J.D.C.. - : ediPUCRS, 2014 BASE Show details 29 Comparing the quality of focused crawlers and of the translation resources obtained from them Laranjeira, B.R.; Moreira, V.P.; Villavicencio, A.. - : European Language Resources Association (ELRA), 2014 BASE Show details 30 Nothing like good old frequency: Studying context filters for distributional thesauri Padró, M.; Idiart, M.; Ramisch, C.. - : Association for Computational Linguistics, 2014 BASE Show details 31 Language acquisition and probabilistic models : keeping it simple Villavicencio, A.; Malioutov, I.; Idiart, M.. - : Association for Computational Linguistics (ACL), 2013 BASE Show details Page: 1 2

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