• CIKM 2013推荐系统论文总结


    这几天在家没事,介绍几篇CIKM上关于推荐系统的文章,

    Personalized Influence Maximization on Social Networks 

    Social Recommendation Incorporating Topic Mining and Social Trust Analysis

           文中作者引入topic的概念,对user, item, tag, trust的关系从topic的角度上从新解释了一遍,最后在PMF的框架上进行求解。

    Location Recommendation for Out-of-Town Users in Location-Based Social Networks

    FRec: A Novel Framework of Recommending Users and Communities in Social Media

    Personalized Point-of-Interest Recommendation by Mining Users' Preference Transition

    GAPfm: Optimal Top-N Recommendations for Graded Relevance Domains

    Community-Based User Recommendation in Uni-Directional Social Networks

    Interactive Collaborative Filtering

          文中介绍了一种交互式的协同过滤算法(在只有评分没有内容的条件下),通过扩展PMF方法构建了随时间变化的概率模型。

  • 相关阅读:
    IO复习
    递归
    转换流
    编码与解码
    打印流(printStream)
    Properties
    【转】将Visual Studio武装到底
    【转】VS2008中的自定义格式化代码
    C++开发工具的常用插件
    抽烟的注意事项
  • 原文地址:https://www.cnblogs.com/guolei/p/3473034.html
Copyright © 2020-2023  润新知