/**
* Create final clusters by merging base clusters and pruning their labels. Cluster merging is a
* greedy process of compacting clusters with document sets that overlap by a certain ratio. In
* other words, phrases that "cover" nearly identical document sets will be conflated.
*/
private ArrayList<ClusterCandidate> createMergedClusters(
ArrayList<ClusterCandidate> baseClusters) {
/*
* Calculate overlap between base clusters first, saving adjacency lists for
* each base cluster.
*/
// [i] - next neighbor or END, [i + 1] - neighbor cluster index.
final int END = -1;
final IntStack neighborList = new IntStack();
neighborList.push(END);
final int[] neighbors = new int[baseClusters.size()];
final float m = (float) mergeThreshold;
for (int i = 0; i < baseClusters.size(); i++) {
for (int j = i + 1; j < baseClusters.size(); j++) {
final ClusterCandidate c1 = baseClusters.get(i);
final ClusterCandidate c2 = baseClusters.get(j);
final float a = c1.cardinality;
final float b = c2.cardinality;
final float c = BitSet.intersectionCount(c1.documents, c2.documents);
if (c / a > m && c / b > m) {
neighborList.push(neighbors[i], j);
neighbors[i] = neighborList.size() - 2;
neighborList.push(neighbors[j], i);
neighbors[j] = neighborList.size() - 2;
}
}
}
/*
* Find connected components in the similarity graph using Tarjan's algorithm
* (flattened to use the stack instead of recursion).
*/
final int NO_INDEX = -1;
final int[] merged = new int[baseClusters.size()];
Arrays.fill(merged, NO_INDEX);
final ArrayList<ClusterCandidate> mergedClusters =
Lists.newArrayListWithCapacity(baseClusters.size());
final IntStack stack = new IntStack(baseClusters.size());
final IntStack mergeList = new IntStack(baseClusters.size());
int mergedIndex = 0;
for (int v = 0; v < baseClusters.size(); v++) {
if (merged[v] != NO_INDEX) continue;
// Recursively mark all connected components from an unmerged cluster.
stack.push(v);
while (stack.size() > 0) {
final int c = stack.pop();
assert merged[c] == NO_INDEX || merged[c] == mergedIndex;
if (merged[c] == mergedIndex) continue;
merged[c] = mergedIndex;
mergeList.push(c);
for (int i = neighbors[c]; neighborList.get(i) != END; ) {
final int neighbor = neighborList.get(i + 1);
if (merged[neighbor] == NO_INDEX) {
stack.push(neighbor);
} else {
assert merged[neighbor] == mergedIndex;
}
i = neighborList.get(i);
}
}
mergedIndex++;
/*
* Aggregate documents from each base cluster of the current merge, compute
* the score and labels.
*/
mergedClusters.add(merge(mergeList, baseClusters));
mergeList.clear();
}
/*
* Sort merged clusters.
*/
Collections.sort(
mergedClusters,
new Comparator<ClusterCandidate>() {
public int compare(ClusterCandidate c1, ClusterCandidate c2) {
if (c1.score < c2.score) return 1;
if (c1.score > c2.score) return -1;
if (c1.cardinality < c2.cardinality) return 1;
if (c1.cardinality > c2.cardinality) return -1;
return 0;
};
});
if (mergedClusters.size() > maxClusters) {
mergedClusters.subList(maxClusters, mergedClusters.size()).clear();
}
return mergedClusters;
}
