This issue of Science China Physics, Mechanics ＆ Astronomy celebrates the Centenary of Einstein＇s General Theory of Rela- tivity, which changed the way humanity understood the concepts of space, time and matter. Prior to 1915 Einstein had intro- duced his theory of Special Relativity, and Minkowski had introduced the spacetime metric. General Relativity overthrew the Newtonian idea that space, time and matter were independent, replacing it with the idea that space, time and matter are inex- tricably linked. Within a year of the publication of General Relativity came Schwartzchild＇s exact solution of Einstein＇s field equations which describes the spacetime structure of black holes. In 1916 and 1918 Einstein showed that his theory predicted the existence of gravitational waves. Within 7 years, in 1922, Friedmann published a solution for Einstein＇s field equations applied to a homogeneous universe, uncovering the basic physics of Big Bang cosmology.
复杂网络的主题社区挖掘具有重要的应用价值,但现有方法可扩展性差,无法高效挖掘大规模复杂网络的主题社区.针对该问题,提出一种基于分布式非负矩阵分解的主题社区挖掘方法:TCMDNMF(topic community mining based on distributed nonnegative matrix factorization),该方法基于非负矩阵联合分解模型,可以有效统一集成节点链接和内容信息挖掘主题社区.通过采用梯度下降方法对主题社区挖掘模型进行了优化求解,并引入L1范数作为稀疏性正则项以及基于Map Reduce分布式计算框架提高了关键算法的计算效率.实验结果表明,TCMDNMF不仅可以有效挖掘主题社区,而且具有高度可扩展性,可以有效解决大规模复杂网络主题社区挖掘带来的大数据量计算问题.
