摘要
针对用户在社交网络中面对海量的信息和资源,如何实时地获取自己感兴趣的内容,给出一种基于社交网络的实时搜索模型,并根据社交网络的特点考虑对朋友、时间、相关度等因子对搜索结果进行排序。针对基于超链接网页排名的Pager-ank算法,提出了一种基于用户朋友数的Pagerank排序算法。实测结果表明,该模型提高了搜索结果的实时性和相关度。
For users of social networks in the face of a flood of information and resources to real-time access to content of interest, a social network is give based real-time search model, and in accordance with social networking features to consider friends, time, relevance and other factors to sort the search results. For the hyperlink-based page ranking Pagerank algorithm, a number of user-based friends Pagerank mental results show that the model improves the real-time and relevance of sorting algorithm is presented. the search results. Experi
出处
《科学技术与工程》
2011年第28期6879-6882,共4页
Science Technology and Engineering
