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首页> 外文期刊>Journal of information and computational science >New Friend Recommendation with User Interest and Socialization
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New Friend Recommendation with User Interest and Socialization

机译：具有用户兴趣和社交性的新朋友推荐

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摘要

Friend recommendation is popular in social site to help people make new friends and expand their social networks. However, the conventional friend recommendation method is low accuracy for the sparsity of data and cold start. To solve this problem, we propose a new personalized recommendation method with user interest and socialization. This approach incorporating user interest and social information mainly leverages both user-based collaborative filtering method and user topological structure in social networks. Firstly, user interest degree can be obtained to identify the user preferences. Secondly, get the new optimized similarity degree and the target user's nearest neighbor by using social collaborative filtering algorithm. In the end, the final recommendation set of user can be acquired from the highest predicted rating of the candidate collection. The experiments indicate that this proposed method can enhance the effectiveness and accuracy of recommendation compared with the traditional friend recommendation algorithm.
机译：推荐朋友在社交网站中很流行，可以帮助人们结交新朋友并扩展他们的社交网络。但是，传统的朋友推荐方法对于数据稀疏和冷启动的准确性较低。为了解决这个问题，我们提出了一种新的具有用户兴趣和社交性的个性化推荐方法。这种结合了用户兴趣和社交信息的方法主要利用了基于用户的协作过滤方法和社交网络中的用户拓扑结构。首先，可以获得用户兴趣度以识别用户偏好。其次，通过社交协作过滤算法获得新的优化相似度和目标用户的最近邻居。最后，可以从候选集合的最高预测评分中获取用户的最终推荐集。实验表明，与传统的好友推荐算法相比，该方法可以提高推荐的有效性和准确性。

著录项

  • 来源
    《Journal of information and computational science》 |2015年第11期|4253-4262|共10页
  • 作者

    Guoyan Huang; Yixin Chang; Yakun Li;

  • 作者单位

    College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China,The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004, China;

    College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China,The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province Qinhuangdao 066004, China;

    College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Recommendation System; Socialization; Similarity; Interest Degree; Collaborative Filtering;

    机译：推荐系统;社会化;相似;兴趣度;协同过滤;

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