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Apache Spark Graph Processing by Rindra Ramamonjison

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The network centrality and PageRank

Previously, we have used the degree distribution and clustering coefficients of a network to understand how connected a network is. In particular, we have learned how to find the largest connected components and the nodes that have the highest degree. Then, we visualized the networks and saw the nodes that have higher chances to play the role of hubs in the network since many nodes are connected to them. In some sense, the degree of a node can be interpreted as a centrality measure that determines how important that node is relative to the rest of the network. In this section, we are going to introduce a different centrality measure as well as the PageRank algorithm, which is useful for ranking nodes in graphs. ...

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