From the Internet to networks of friendship, disease transmission, and even terrorism, the concept - and the reality - of networks has come to pervade modern society. But what exactly is a network? What different types of networks are there? Why are they interesting, and what can they tell us? In recent years, scientists from a range of fields - including mathematics, physics, computer science, sociology, and biology - have been pursuing these questions and building a new 'science of networks.' This book brings together, for the first time, a set of seminal articles representing research from across these disciplines. It is an ideal sourcebook for the key research in this fast-growing field. The book is organized into four sections, each preceded by an editors' introduction summarizing its contents and general theme. The first section sets the stage by discussing some of the historical antecedents of contemporary research in the area. From there the book moves to the empirical side of the science of networks before turning to the foundational modeling ideas that have been the focus of much subsequent activity. The book closes by taking the reader to the cutting edge of network science - the relationship between network structure and system dynamics. From network robustness to the spread of disease, this section offers a potpourri of topics on this rapidly expanding frontier of the new science.
这本书是一个论文集,摘录了自98年瓦茨等研究以来的复杂网络研究中的精彩论文,是尝试了解复杂网络研究的必读之书。 复杂网络研究将对网络的理解扩展了很多。~····························~
評分这本书是一个论文集,摘录了自98年瓦茨等研究以来的复杂网络研究中的精彩论文,是尝试了解复杂网络研究的必读之书。 复杂网络研究将对网络的理解扩展了很多。~····························~
評分这本书是一个论文集,摘录了自98年瓦茨等研究以来的复杂网络研究中的精彩论文,是尝试了解复杂网络研究的必读之书。 复杂网络研究将对网络的理解扩展了很多。~····························~
評分这本书是一个论文集,摘录了自98年瓦茨等研究以来的复杂网络研究中的精彩论文,是尝试了解复杂网络研究的必读之书。 复杂网络研究将对网络的理解扩展了很多。~····························~
評分这本书是一个论文集,摘录了自98年瓦茨等研究以来的复杂网络研究中的精彩论文,是尝试了解复杂网络研究的必读之书。 复杂网络研究将对网络的理解扩展了很多。~····························~
幾個核心概念在wiki上一頁就概括瞭。山頭的人主要還是想看看能不能用工具來預測新世界。然鵝後來ML和DL的井噴發展後,就沒人在純粹去看network結構本身瞭,而是變成瞭研究對象
评分幾個核心概念在wiki上一頁就概括瞭。山頭的人主要還是想看看能不能用工具來預測新世界。然鵝後來ML和DL的井噴發展後,就沒人在純粹去看network結構本身瞭,而是變成瞭研究對象
评分比newman自己寫的那本networks讀起來更爽。
评分幾個核心概念在wiki上一頁就概括瞭。山頭的人主要還是想看看能不能用工具來預測新世界。然鵝後來ML和DL的井噴發展後,就沒人在純粹去看network結構本身瞭,而是變成瞭研究對象
评分相比越來越深的deep learning 還是complex network一派的研究更elegant
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