Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings

IJCNLP 2019 Philippa ShoemarkFarhana Ferdousi LizaDong NguyenScott HaleBarbara McGillivray

Word embeddings are increasingly used for the automatic detection of semantic change; yet, a robust evaluation and systematic comparison of the choices involved has been lacking. We propose a new evaluation framework for semantic change detection and find that (i) using the whole time series is preferable over only comparing between the first and last time points; (ii) independently trained and aligned embeddings perform better than continuously trained embeddings for long time periods; and (iii) that the reference point for comparison matters... (read more)

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