Summary

In this chapter, we looked at:

  • Graph mining. We also saw that the characteristics of graph data can be divided into frequent pattern mining, classification, and clustering
  • Mining frequent subgraph patterns is done to find the frequent patterns in a set of graphs or a single massive graph
  • Social network analysis includes a wide range of web applications with broad definitions, such as Facebook, LinkedIn, Google+, StackOverflow, and so on

In the next chapter, we will focus on the major topics related to web mining and algorithms and look at some examples based on them.

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