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Papers

UWB @ DIACR-Ita: Lexical Semantic Change Detection with CCA and Orthogonal Transformation

2020-11-30 · Ondřej Pražák, Pavel Přibáň, Stephen Taylor

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 $1^{st}$. 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.

📄 PDF Abstract BibTeX arXiv:2011.14678

Code (1)

pauli31/SemEval2020-task1 공식 구현

Tasks

Change Detection

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UWB at SemEval-2020 Task 1: Lexical Semantic Change Detection

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