Linear transformations for cross-lingual semantic textual similarity

作者：

Highlights：

• Linear transformations project monolingual semantic spaces into a shared space.

• We propose a new transformation outperforming others in the cross-lingual STS task.

• We extend unsupervised STS methods by the word weighting.

• Our approach achieves promising results on several datasets in different languages.

摘要

•Linear transformations project monolingual semantic spaces into a shared space.•We propose a new transformation outperforming others in the cross-lingual STS task.•We extend unsupervised STS methods by the word weighting.•Our approach achieves promising results on several datasets in different languages.

论文关键词：Semantic textual similarity,Semantic spaces,Linear transformations,Word embeddings,Cross-lingual semantic spaces

论文评审过程：Received 17 October 2018, Revised 3 March 2019, Accepted 26 June 2019, Available online 27 June 2019, Version of Record 18 November 2019.

论文官网地址：https://doi.org/10.1016/j.knosys.2019.06.027