論文筆記：Network Representation Learning with Rich Text Information
network representation learning with rich text information 時間倉促，沒有特別仔細的看（之後再更新） 論文的成果有兩點： 證明deepwalk其實就等價於matrix factorization（DW可以用MF表示） 其中，W矩陣是在skip-gram中中心詞的表達，H是上下文的表達。 M在使用softmax的時候是log（詞對（vi，ci
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相關文章
- 1. 論文筆記：Representation Learning with Contrastive Predictive Coding
- 2. NRL: network representation learning & NE: network embedding. 相關論文總結
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- 5. 【論文筆記】NRL-Heterogeneous Information Network
- 6. 【論文筆記】Learning Deconvolution Network for Semantic Segmentation
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