Question

I am implementing a Flame clustering algorithm as a way of learning a bit more about graphs and graph traversal, and one of the first steps is constructing a K-nearest-neighbors graph, and I’m wondering what the fastest way would be of running through a list of nodes and connecting each one only to say, it’s nearest five neighbors. My thought was that I would start at a node, iterate through the list of other nodes and keep the ones that are closest within an array, making sure that everything past the top n are discarded. Now, I could do this by just sorting a list and keeping the top n entries, but I would much rather keep less fewer things in memory and so I was wondering if there was a way to just have the final array and update that array as I iterate through, or if there is a more efficient way of generating a k nearest neighbors graph.

Also, please note, this is NOT a duplicate of K-Nearest Neighbour Implementation in Java. KNNG is distinct from KNN.

Answer 1

Place the first n nodes, sorted in a List. Then iterate through the rest of nodes and if it fits in the current list (i.e. is a top n node), place it in the corresponding position in the list and discard the last top n node. If it doesn’t fit in the top n list, discard it.

for each neighborNode
 for(int i = 0; i < topNList.size(); i++){
       if((dist = distanceMetric(neighborNode,currentNode)) > topNList.get(i).distance){
             topNList.remove(topNList.size()-1)
             neighborNode.setDistance(dist);
             topNList.add(i, neighborNode);
       }