Unsupervised User Identity Linkage via Factoid Embedding 閱讀筆記
無監督的用戶對齊學習 Unsupervised User Identity Linkage via Factoid Embedding 鏈接地址 https://arxiv.org/pdf/1901.06648.pdf 摘要 其關鍵思想是關於用戶標識的每條信息都描述了真實情況標識所有者，從而將所有者與其他用戶區分開來。我們用factoid表示這樣一條信息，並將其建模爲由用戶標識、謂詞和組成的三元組
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相關文章
- 1. DPLink: User Identity Linkage via Deep Neural Network From Heterogeneous Mobility Data 閱讀筆記
- 2. Graph Neural Networks for User Identity Linkage 2019 論文閱讀筆記
- 3. CoLink: An Unsupervised Framework for User Identity Linkage
- 4. Instance Embedding Transfer to Unsupervised Video Object Segmentation閱讀筆記
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- 6. 《Predict Anchor Links across Social Networks via an Embedding Approach》閱讀筆記
- 7. NASE Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search 閱讀筆記
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- 9. 論文閱讀：Collaborative Deep Embedding Via Dual Networks
- 10. Unsupervised Personalized Feature Selection--閱讀筆記