Nearest neighbors relationships are part of Jacquez's k-Nearest Neighbor (k-NN).
Jacquez's k-NN method considers temporal adjacency to evaluate clustering. It categorizes whether events neighbor each other in space and time. ClusterSeer calculates nearest neighbor relationships in time by placing the events in a dataset in chronological order. The nearest neighbor of an event is the prior event, as illustrated in the diagram below. Because the nearest neighbor is always the prior event, nearest neighbor relationships in time are never reciprocal, unlike spatial nearest neighbors.
A point has a nearest neighbor, but nearest neighbor relationships can be considered at higher levels. The nearest neighbor methods in ClusterSeer are flexible and can consider several levels of neighbors (first nearest neighbor, first and second nearest neighbor, etc.). k defines the number of neighbors to consider in the analysis. In the illustration below, 4 & 5 are the two nearest neighbors of 6.
A problem with nearest neighbor methods is how to resolve ties. If two neighbors are the same time from the event considered, which one should be scored? A problem with nearest neighbor methods is how to resolve ties. If two neighbors are the same distance from the event considered, which one should be scored? ClusterSeer solves the tie arbitrarily by choosing only one of the tied events.
