解析单词 polysemy/homonymy 的最先进算法是什么？
What are the state-of-art algorithms for resolving words polysemy/homonymy?
我试图通过类似 word2vec 的神经网络 () 解决单词多义问题（修复文本中多义词的 WordNet 同义词集），但结果太差。
解析单词 polysemy/homonymy 的其他最先进算法是什么？你能给我一些文章吗？
您可以从 spacy's implementation of sense2vec. It is based on the original sense2vec paper 开始。来自摘要：
This paper presents a novel approach which addresses these concerns by modeling multiple embeddings for each word based on supervised disambiguation, which provides a fast and accurate way for a consuming NLP model to select a sense-disambiguated embedding. We demonstrate that these embeddings can disambiguate both contrastive senses such as nominal and verbal senses as well as nuanced senses such as sarcasm.
在 this page you can find NLP STATE-OF-THE-ART publications and rank, particularly word sense disambiguation - WSD SOTA. You might be interested on supWSDemb 和
UKB分别是当前时间的有监督和无监督SOTA。
我试图通过类似 word2vec 的神经网络 (
您可以从 spacy's implementation of sense2vec. It is based on the original sense2vec paper 开始。来自摘要：
This paper presents a novel approach which addresses these concerns by modeling multiple embeddings for each word based on supervised disambiguation, which provides a fast and accurate way for a consuming NLP model to select a sense-disambiguated embedding. We demonstrate that these embeddings can disambiguate both contrastive senses such as nominal and verbal senses as well as nuanced senses such as sarcasm.
在 this page you can find NLP STATE-OF-THE-ART publications and rank, particularly word sense disambiguation - WSD SOTA. You might be interested on supWSDemb 和 UKB分别是当前时间的有监督和无监督SOTA。