信息检索原理课件-[转帖]复杂网络入门最佳资料：英文经典综述合集课外天地李树青

从我自己的经验来说，读优秀的综述论文是进入一个方向最便捷的途径。

我曾经写过一篇文章，叫做《复杂网络入门读物》，实际上是以前中英文综述的一个综述。在一个很细分的领域里拥有40000+的阅读量，很多人认识我恐怕是因为看了这个博客。

现在，复杂网络又往前走了五年，我想从五个方面为大家梳理一下最重要的参考资料——这实际上也是服务我和荣智海下半年的一门《网络科学导论》课，以及我们实验室的研究生和本科生。分别是全球重要的综述，中文快速入门的综述，英文和中文的书籍，以及领域突破性的论文。有一些要花的时间非常长，而且可能超过了我的能力，我只能尽力而为了。

（1）发表在大家公认的顶尖杂志上，例如物理学的三大综述期刊（Rev. Mod. Phys., Phys. Rep. 和Adv. Phys.），以及Nature、NaturePhysics、Science和Nature Reviews系列上的综述论文；

（2）发表后引用超过1000次的论文（本文的引用数据来自Google Scholar，截止到解放军建军90周年）。

有些综述论文我个人特别喜欢，例如最近在J. Complex Networks和我过Nat. Sci. Rev.上的一些工作。但是为了避免带入太多个人色彩，我都没有选入。如果这些论文足够好，我相信很快就会引用超过1000次。

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[Liao2017] Liao, H., Mariani, M. S., Medo, M.,Zhang, Y. C., & Zhou, M. Y. (2017). Ranking in evolving complex networks. PhysicsReports, 689, 1-54. [Cited 0 times]

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又比如社团结构是属于网络结构特征的，但是社团挖掘作为一种特殊的数据挖掘算法，更接近网络信息挖掘。

再比如Dorogovtsev在2008年的那篇RMP，绝大部分都是在说动力学临界性，但是又有一些结构的内容，所以放两个类都有道理。

有一些关联很强的综述，例如Clauset等人关于Power law的实证研究，因为不是从网络出发，所以没有选入。

实际上各个分类之间都有公共区域，分到哪里不分到哪里，也没有不容置疑的边界。