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• W3101920900 abstract "Consider a continuous word embedding model. Usually, the cosines between word vectors are used as a measure of similarity of words. These cosines do not change under orthogonal transformations of the embedding space. We demonstrate that, using some canonical orthogonal transformations from SVD, it is possible both to increase the meaning of some components and to make the components more stable under re-learning. We study the interpretability of components for publicly available models for the Russian language (RusVectores, fastText, RDT)." @default.
• W3101920900 created "2020-11-23" @default.
• W3101920900 creator A5027556604 @default.
• W3101920900 date "2017-12-21" @default.
• W3101920900 modified "2023-09-23" @default.
• W3101920900 title "Rotations and Interpretability of Word Embeddings: The Case of the Russian Language" @default.
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• W3101920900 doi "https://doi.org/10.1007/978-3-319-73013-4_11" @default.
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