Traditional approaches to supervised learning require a generous amount of labeled data
for good generalization. While such annotation-heavy approaches have proven useful for …

Multi-sense word embedding is an important extension of neural word embeddings. By
leveraging context of each word instance, multi-prototype version of word embeddings were …

Unsupervised learned representations of polysemous words generate a large of pseudo
multi senses since unsupervised methods are overly sensitive to contextual variations. In …

语料库语言学是借助大规模语料库对语言现象进行发现, 挖掘的研究学科,
目前已经存在很多在线语料库辅助语言学家的研究. 该文提供了一个按时间分片进行管理的 …

In multi-sense word embeddings, contextual variations in corpus may cause a univocal word
to be embedded into different sense vectors. Shi et al.(2016) show that this kind of pseudo …