Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation简析

时间 2019-12-12

标签 relational collaborative filtering modeling multiple item relations recommendation 繁體版

原文原文链接

Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation 介绍做者介绍了一种新颖的基于item的协同过滤框架——关系型的协同过滤，利用two-level的hieraychy将多个item关系利用attention整合造成user preference以及提升item embedd

>>阅读原文<<

1. Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation简析
2. Item-Based Collaborative Filtering Recommendation Algorithms
3. 阅读笔记：Item-based Collaborative Filtering Recommendation Algorithms
4. Deep Item-based Collaborative Filtering for Top-N Recommendation 阅读心得
5. Collaborative Memory Network for Recommendation Systems
6. Neural Collaborative Filtering
7. Item-Based Collaborative Filtering Recommendation Algorithms - 2001年 - 被引用7190次
8. reading notes -- Amazon.com Recommendations: Item-to-Item Collaborative Filtering
9. An Efficient Deep Learning Approach for Collaborative Filtering Recommender System
10. Memory-based的CF推荐--Item-based的方法：Item-Based Collaborative Filtering Recommendation Algorithms
更多相关文章...
• Swift for 循环 - Swift 教程
• Scala for循环 - Scala教程
• RxJava操作符（三）Filtering
• Github 简明教程

最新文章

1. Duang!超快Wi-Fi来袭
2. 机器学习-补充03 神经网络之**函数(Activation Function)
3. git上开源maven项目部署多module maven项目（多module maven+redis+tomcat+mysql）后台部署流程学习记录
4. ecliple-tomcat部署maven项目方式之一
5. eclipse新导入的项目经常可以看到“XX cannot be resolved to a type”的报错信息
6. Spark RDD的依赖于DAG的工作原理
7. VMware安装CentOS-8教程详解
8. YDOOK：Java 项目 Spring 项目导入基本四大 jar 包导入依赖，怎样在 IDEA 的项目结构中导入 jar 包导入依赖
9. 简单方法使得putty（windows10上）可以免密登录树莓派
10. idea怎么用本地maven

本站公众号

欢迎关注本站公众号,获取更多信息

1. Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendation简析
2. Item-Based Collaborative Filtering Recommendation Algorithms
3. 阅读笔记：Item-based Collaborative Filtering Recommendation Algorithms
4. Deep Item-based Collaborative Filtering for Top-N Recommendation 阅读心得
5. Collaborative Memory Network for Recommendation Systems
6. Neural Collaborative Filtering
7. Item-Based Collaborative Filtering Recommendation Algorithms - 2001年 - 被引用7190次
8. reading notes -- Amazon.com Recommendations: Item-to-Item Collaborative Filtering
9. An Efficient Deep Learning Approach for Collaborative Filtering Recommender System
10. Memory-based的CF推荐--Item-based的方法：Item-Based Collaborative Filtering Recommendation Algorithms

>>更多相关文章<<