中文摘要：

为了更好地为广大学者阅读文献提供个性化的推荐服务,针对中国知网学术论文发现科研社区,提出了一种科研社区发现算法：首先利用Pajek构建出科研论文合著网络,并将网络公共数据集Dining-table partners和Sampson作为测试数据集,对科研社区发现算法和社区发现经典算法GN算法进行性能对比分析,验证科研社区发现算法的性能更优;最后利用算法发现科研社区结构,实验结果表明社区划分的效果较好。

英文摘要：

Detecting scientific research community based on CNKI ＇s academic papers could provide personalized recommendation service for reading documents of the majority of scholars. This paper put forward a scientific research community detection algorithm,firstly,established the scientific research paper coauthor network by Pajek,regarded Dining-table partners and Sampson of network common data set as testing data set to have a performance comparison and analysis on the scientific research community detection algorithm and classical GN algorithm,verified that the performance of the scientific research community detection algorithm was more superior and finally found scientific research community structure using the algorithm,and the experimental results showed that the effect of community division was pretty good.