大规模语料库是计算机技术和深度学习理论进步相结合的新产物，使用 word2vec 技术、GloVe 技术构建的语料库是以高维词向量为基本存储单元和最小 分析粒度的绝佳材料，反映了语言学的各种语义关系和多特征的语义信息。本文 利用 GloVe 的开源语料库的高维词向量，构造了高质量高频词差向量空间，并对 其空间特征和基本实例进行了探索。本文完成了对高维差向量空间的降维可视 化，引入了 KNN 搜索方法，并使用蒙特卡罗方法寻找高维空间的高密度区域。

The large-scale corpus is a new product of the combination of computer technology and deep- learning theory. The corpus constructed by word2vec technology and glove technology is an excellent material for high-dimensional word vectors as the basic storage unit and the minimum analysis granu- larity. Corpus reflects the language semantic relations and semantic information of multiple features. This paper makes good use of the high-dimensional word vector of open source corpus of glove to construct a high-quality and high-frequency word difference vector space, and explores its spatial characteristics and basic examples. This paper completes the downscaling visualization of the high- dimensional difference space, introduces the KNN search method, and uses the Monte Carlo method to find high-density areas in the high-dimensional space.