一个基于社会网络的内容推荐模型研究

STUDY ON A SOCIAL NETWORK-BASED CONTENTS RECOMMENDATION MODEL

针对社会网络中缺少有效依据内容的推荐方法,提出基于社会网络的新闻推荐模型,设计了基于社会网络的新闻推荐算法。通过综合新闻内容的浏览时间指标、推介指标、评价指标以及内容的相似度指标,发掘和构建社会网络中的朋友关系,寻找距离最近的朋友,计算综合推荐度,制定出推荐新闻的策略,成功进行了内容推荐。实验表明,该方法适合社会网络中的新闻推荐,也可为社会网络中其它内容推荐提供借鉴。

Social network lacks effective content-based recommendation method, to address this issue, we propose a social network-based news recommendation model, and design a social network-based news recommendation algorithm. By integrating the indices of browsing time, promotion, evaluation and contents similarity in regard to news contents, the algorithm explores and constructs the friendship relations in social network, searches the friends in closest distance, calculates the comprehensive recommendation degree and works out the policy of news recommendation, the content recommendation is then successfully carried out. Experiments show that the method fits the news recommendation in social network, and can also provide reference for other content recommendation in social network.