"斯坦福CS224W复杂网络分析：度分布、路径长度、聚类系数与连通组件"

- The Stanford CS224W course on the Analysis of Networks, taught by Jure Leskovec, focuses on various key concepts in complex network analysis. - One of the main topics covered in the course is the degree distribution of networks, denoted as P(k), which represents the probability that a randomly selected node in the network has a degree of k. - Another important concept discussed is the path length, denoted as h, which refers to the average number of steps it takes to travel from one node to another in the network. - The clustering coefficient, denoted as C, is also examined in the course, which measures the degree to which nodes in the network tend to cluster together. - The course also explores the concept of connected components in networks, which are sets of nodes that are connected to each other by paths but not connected to any other nodes in the network. - Through the study of these concepts and more, students in the course gain valuable insights into the structure and behavior of complex networks, enabling them to better understand and analyze real-world networks such as social networks, biological networks, and technological networks.