Technologies for node-degree based clustering of data sets
Abstract:
Technologies for node-degree based clustering include a computing device to construct a graph that includes multiple vertices corresponding to the data points of a data set. The computing device inserts an edge between each pair of vertices that has a corresponding similarity metric that meets a predetermined threshold similarity metric. The computing device determines a node degree for each vertex in the graph and initializes a cutoff node degree as the lowest node degree of the vertices. The computing device selects a test subset of the graph that includes vertices having a node degree less than or equal to the cutoff node degree. The computing device determines whether the test subset covers the graph and if not increases the cutoff node degree. If the test subset covers the graph, the data points corresponding to the vertices of the test subset are the representative cluster. Other embodiments are described and claimed.
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