论文标题
op-ims @ ducr-ita：返回根源：sgns+op+cd仍然摇滚语义变化检测
OP-IMS @ DIACR-Ita: Back to the Roots: SGNS+OP+CD still rocks Semantic Change Detection
论文作者
论文摘要
我们介绍了参与diacr-ita共享的任务的结果，该任务涉及意大利语的词法语义变化检测。我们利用基于Skip-gram的最早，最具影响力的语义变化检测模型之一，具有负抽样，正交倾向对准和余弦距离，并以接近到完美的精度获得共享任务的获胜提交.94。我们的结果再次表明，在词汇语义变化检测中的当前任务设置中，传统的基于类型的方法产生了出色的性能。
We present the results of our participation in the DIACR-Ita shared task on lexical semantic change detection for Italian. We exploit one of the earliest and most influential semantic change detection models based on Skip-Gram with Negative Sampling, Orthogonal Procrustes alignment and Cosine Distance and obtain the winning submission of the shared task with near to perfect accuracy .94. Our results once more indicate that, within the present task setup in lexical semantic change detection, the traditional type-based approaches yield excellent performance.
