本课程是学校课程之一,正好自己比较感兴趣然后就多学了一些(主要还是听不懂学校老师讲的……:joy: )
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本课设为TYUT 设立的NLP 课设的答辩讲稿与设计流程实现
Recent methods for learning vector space representations of words have succeeded in capturing fine-grained semantic and syntactic regularities using vector arithmetic, but the origin of these regularities has remained opaque. We analyze and make explicit the model properties needed for such regularities to emerge in word vectors. The result is a new ==global log-bilinear regression model== that combines the advantages of the two major model families in the literature: global matrix factorization and local context window methods. Our model efficiently leverages statistical information by ==training only on the nonzero elements in a word-word co-occurrence matrix==, rather than on the entire sparse matrix or on individual context windows in a large corpus. The model produces a vector space with meaningful substructure, as evidenced by its performance of 75% on a recent word analogy task. It also outperforms related models on similarity tasks and named entity recognition.
more >>Welcome to Hexo! This is your very first post. Check documentation for more info. If you get any problems when using Hexo, you can find the answer in troubleshooting or you can ask me on GitHub.
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缺失模块。
1、请确保node版本大于6.2
2、在博客根目录(注意不是yilia根目录)执行以下命令:
npm i hexo-generator-json-content --save
3、在根目录_config.yml里添加配置:
jsonContent: meta: false pages: false posts: title: true date: true path: true text: false raw: false content: false slug: false updated: false comments: false link: false permalink: false excerpt: false categories: false tags: true