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11 mai 2021
- doi: 10.4000/books.aaccademia.7800
- eisbn: 9791280136329
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
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EVALITA COVID-19 Infodemic linguistica computazionale Automatic Misogyny Identification Misogyny on Twitter Posts AlBERTo Convolutional Neural Network BERT Model Hate Speech Detection Multimodal Meme Detection MEME management Language Game ``La Ghigliottina'' Language & Linguistics LAN000000 CBXSujets proches
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Ondřej Pražák et al., « UWB @ DIACR-Ita: Lexical Semantic Change Detection with CCA and Orthogonal Transformation », Accademia University Press, ID : 10.4000/books.aaccademia.7800
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In this paper, we describe our method for detection of lexical semantic change (i.e., word sense changes over time) for the DIACR-Ita shared task, where we ranked 1st. We examine semantic differences between specific words in two Italian corpora, chosen from different time periods. Our method is fully unsupervised and language independent. It consists of preparing a semantic vector space for each corpus, earlier and later. Then we compute a linear transformation between earlier and later spaces, using CCA and Orthogonal Transformation. Finally, we measure the cosines between the transformed vectors.