论文阅读 KGAT: Knowledge Graph Attention Network for Recommendation
1. Motivation 如何将side information和用户-物品二部图考虑在一起给用户提供准确、多样和可解释的推荐是非常有必要的。目前基于CF的方法并不能很好的对用户和物品的side information进行建模，这样就不可避免的面临数据稀疏性的问题。工业界的解决办法是使用监督学习模型，比如FM，NFM，wide&deep等方法去将用户物品的所有side information看成
相关文章
- 1. 20200427 Knowledge Graph Attention Network for Recommendation
- 2. Side Information-KGAT: Knowledge Graph Attention Network for Recommendation阅读笔记
- 3. 【论文翻译】KGAT: Knowledge Graph Attention Network for Recommendation
- 4. Knowledge Graph Attention Network for Recommendation
- 5. Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph
- 6. 论文阅读《Graph Contextualized Self-Attention Network for Session-based Recommendation》
- 7. RKGE Recurrent Knowledge Graph Embedding for Effective Recommendation 论文
- 8. DKN: Deep Knowledge-Aware Network for News Recommendation阅读笔记
- 9. Residual Attention Network for Image Classification 论文阅读
- 10. 《Graph Attention Network》阅读笔记
- 更多相关文章...
- • RSS 阅读器 - RSS 教程
- • PHP 实例 - AJAX RSS 阅读器 - PHP教程
- • JDK13 GA发布：5大特性解读
- • Scala 中文乱码解决
相关标签/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
欢迎关注本站公众号,获取更多信息
相关文章
- 1. 20200427 Knowledge Graph Attention Network for Recommendation
- 2. Side Information-KGAT: Knowledge Graph Attention Network for Recommendation阅读笔记
- 3. 【论文翻译】KGAT: Knowledge Graph Attention Network for Recommendation
- 4. Knowledge Graph Attention Network for Recommendation
- 5. Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph
- 6. 论文阅读《Graph Contextualized Self-Attention Network for Session-based Recommendation》
- 7. RKGE Recurrent Knowledge Graph Embedding for Effective Recommendation 论文
- 8. DKN: Deep Knowledge-Aware Network for News Recommendation阅读笔记
- 9. Residual Attention Network for Image Classification 论文阅读
- 10. 《Graph Attention Network》阅读笔记