public void test() {
mimaGraph graph = new mimaGraph();
loadGraph load = new loadGraph();
load.readData(graph, "Brightkite_edges.txt", 0, "\t");
load.wcProb(graph);
graph.setUniformShareProb(0.9);
int[] seed =
new int[] {
29024, 16518, 35558, 34792, 33833, 8201, 1517, 10382, 33806, 23728, 35026, 84, 19380,
24310, 34295, 2106, 17114, 4698, 827, 16188
};
Set<Integer> seedSet = new HashSet<Integer>();
for (int s : seed) seedSet.add(s);
seedSet = graph.read2Seed("BrightkiteSeed.txt");
System.out.println("avg=" + this.avgMic(1000, seedSet, graph));
this.printActResult(10, "set");
}
public Set<Integer> greedyMIC(
int k, String dataset, String cascadeProb, double retweetAgainProb) {
mimaGraph graph = new mimaGraph();
loadGraph load = new loadGraph();
load.readData(graph, dataset, 1, "\t");
if (cascadeProb.toLowerCase().contains("w")) load.wcProb(graph);
else if (cascadeProb.toLowerCase().contains("un")) load.uniformProb(graph, 0.3);
graph.setUniformShareProb(retweetAgainProb);
/////////////////////////////
System.out.println("This is greedy algorithm in MIC model.");
System.out.println(
"Data: "
+ dataset
+ "\tcascade: "
+ cascadeProb
+ "\tretweet probability: "
+ retweetAgainProb);
Set<Integer> seed = new HashSet<Integer>();
sortedVertices sv = new sortedVertices();
for (int i = 0; i < k; i++) {
for (int id : graph.getAllIDs()) {
if (seed.contains(id)) continue;
seed.add(id);
sv.add(new simpleVertex(id, this.avgMic(seed, graph)));
seed.remove(id);
}
seed.add(sv.max().getID());
System.out.print(sv.max().getID() + " ");
sv.clear();
}
return seed;
}
