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Wilson, K., Green, N., Agrawal, L., Gao, X., Madhusoodanan, D., Riley, B., & Sigmon, J. (2013). Graph-based proximity measures. In N. F. Samatova, W. Hendrix, J. Jenkins, K. Padmanabhan, & A. Chakraborty (Eds.), Practical graph mining with R (1st ed., pp. 135-166). Springer.
In order to apply several different graph-based data mining techniques like classification and clustering (discussed further in Chapter 9 Classification, first graph). This on within-graph proximity measures that will be used in the application of several data mining techniques later in the book. We introduce two different algorithms for measuring proximity between vertices in a graph: 1. Shared Nearest Neighbor (SNN). Shared Nearest Neighbor defines proximity, or similarity, between two vertices in terms of the number of neighbors (i.e., directly connected vertices) they have in common. SNN is described in detail in Section 6.2.3.