Cross-domain Recommendation Without sharing User-relevant Data簡析
Cross-domain Recommendation Without sharing User-relevant Data 介紹 爲了聯合不一樣網站的相同數據以提升 推薦質量，可是爲了不商業隱私，文章不使用用戶相關的數據，而僅僅使用item的信息，同時爲了有效的發掘有用的信號，文章使用了一種新的方法NATR（Neural Attentive Transfer Recommendation）htm
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相關文章
- 1. Cross-domain Recommendation Without sharing User-relevant Data簡析
- 2. Multi Institution Deep Learning Modeling Without Sharing Patient Data
- 3. NARM:Neural Attentive Session-based Recommendation簡析
- 4. 【Salesforce】【Developer】 Apex study --difference between with sharing and without sharing
- 5. SFDC:關於with sharing和without sharing 關鍵字聲明Apex類，涉及到的CRUD/FLS/SHARING的個人總結
- 6. Backup App's data without rooting the phone
- 7. Sequential Scenario-Specific Meta Learner for Online Recommendation簡析
- 8. DKN: Deep Knowledge-Aware Network for News Recommendation簡析
- 9. NAIS: Neural Attentive Item Similarity Model for Recommendation簡析
- 10. Feature Re-Learning with Data Augmentation for Content-based Video Recommendation簡介