首页> 外文会议>International Conference on Intelligent Information Hiding and Multimedia Signal Processing >An Improved Collaborative Filtering Recommendation Algorithm for Microblog Based on Community Detection
【24h】

An Improved Collaborative Filtering Recommendation Algorithm for Microblog Based on Community Detection

机译:基于社区检测的微博微博协作滤波推荐算法

获取原文

摘要

With the rapid development of mobile Internet and the explosive growth of intelligent mobile terminals, microblog has become indispensable in many people's daily life but also bring overload information. A recommender system is needed but the traditional collaborative filtering recommendation algorithm is suffered from two main problems here: data sparsity and user relationship influence. In this paper, we proposed an improved collaborative filtering algorithm based on community detection for microblog recommendation. We apply the community detection algorithm to analysis the structure of the user relationship network in microblog before we do the recommendation. We make some adjustments to help the collaborative filtering algorithm works better in the community based system. Results of experimental evaluation demonstrate that in a microblog network, our algorithm remarkably outperforms the traditional collaborative filtering scheme by enhancing the recommendation accuracy.
机译:随着移动互联网的快速发展和智能移动终端的爆炸性增长,微博在许多人的日常生活中变得不可或缺,但也会带来超载信息。需要推荐系统,但传统的协作过滤推荐算法在这里有两个主要问题:数据稀疏性和用户关系影响。本文提出了一种基于社区检测的改进的协作滤波算法,用于微博推荐。我们应用社区检测算法在我们执行建议之前分析微博中的用户关系网络的结构。我们进行了一些调整,帮助协作过滤算法在基于社区的系统中更好地工作。实验评估结果表明,在微博网络中,我们的算法通过提高推荐准确性来显着优于传统的协作滤波方案。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号