/****************************** Constructor **********************************/
// Personalized PageRank Algorithm: All node do random jump to Ego node
public Model(Graph graph, double dampingFactor, int targetNode)
{
this.linkMatrix = graph.matrix;
this.nNodes = graph.getCntAllNodes();
this.dampingFactor = dampingFactor;
this.egoNode = targetNode;
rank = new double[nNodes];
nextRank = new double[nNodes];
for (int i = 0; i < nNodes; i++)
{
// Initialize rank score of each node
rank[i] = (i == targetNode) ? nNodes : 0;
nextRank[i] = 0;
}
}
/****************************** Constructor **********************************/
// Personalized PageRank Algorithm: All node do random jump to Ego node
public Model(Graph graph, double dampingFactor, int targetNode)
{
this.linkMatrix = graph.matrix;
this.nNodes = graph.getCntAllNodes();
this.dampingFactor = dampingFactor;
this.egoNode = targetNode;
rank = new double[nNodes];
nextRank = new double[nNodes];
for (int i = 0; i < nNodes; i++)
{
// Initialize rank score of each node
rank[i] = (i == targetNode) ? nNodes : 0;
nextRank[i] = 0;
}
}
public Model(Graph graph, double dampingFactor, int targetNode)
{
this.graph = graph;
this.nNodes = graph.getCntAllNodes();
this.dampingFactor = dampingFactor;
rank = new double[nNodes];
nextRank = new double[nNodes];
restart = new double[nNodes];
for (int i = 0; i < nNodes; i++)
{
// Initialize rank score of each node
rank[i] = (i == targetNode) ? nNodes : 0;
nextRank[i] = 0;
// Make restart weight
restart[i] = (i == targetNode) ? 1d : 0; // [1, 0, 0, 0, 0, ... , 0, 0, 0]: Personalized PageRank
}
}
public Model(Graph graph, double dampingFactor, int targetNode)
{
this.graph = graph;
this.nNodes = graph.getCntAllNodes();
this.dampingFactor = dampingFactor;
rank = new double[nNodes];
nextRank = new double[nNodes];
restart = new double[nNodes];
for (int i = 0; i < nNodes; i++)
{
// Initialize rank score of each node
rank[i] = (i == targetNode) ? nNodes : 0;
nextRank[i] = 0;
// Make restart weight
restart[i] = (i == targetNode) ? 1d : 0; // [1, 0, 0, 0, 0, ... , 0, 0, 0]: Personalized PageRank
}
}
