org.jgrapht.alg.linkprediction.ResourceAllocationIndexLinkPrediction Maven / Gradle / Ivy
/*
* (C) Copyright 2020-2021, by Dimitrios Michail and Contributors.
*
* JGraphT : a free Java graph-theory library
*
* See the CONTRIBUTORS.md file distributed with this work for additional
* information regarding copyright ownership.
*
* This program and the accompanying materials are made available under the
* terms of the Eclipse Public License 2.0 which is available at
* http://www.eclipse.org/legal/epl-2.0, or the
* GNU Lesser General Public License v2.1 or later
* which is available at
* http://www.gnu.org/licenses/old-licenses/lgpl-2.1-standalone.html.
*
* SPDX-License-Identifier: EPL-2.0 OR LGPL-2.1-or-later
*/
package org.jgrapht.alg.linkprediction;
import java.util.HashSet;
import java.util.List;
import java.util.Objects;
import java.util.Set;
import org.jgrapht.Graph;
import org.jgrapht.Graphs;
import org.jgrapht.alg.interfaces.LinkPredictionAlgorithm;
import org.jgrapht.alg.util.Pair;
/**
* Predict links using the Resource Allocation Index.
*
*
* This is a local method which computes $s_{uv} = \sum_{z \in
* \Gamma(u)\cap\Gamma(v))}\frac{1}{k(z)}$ where for a node $v$, $\Gamma(v)$ denotes the set of
* neighbors of $v$ and $k(v) = |\Gamma(v)|$ denotes the degree of $v$.
*
*
* See the following two papers:
*
* - Liben‐Nowell, David, and Jon Kleinberg. "The link‐prediction problem for social networks."
* Journal of the American society for information science and technology 58.7 (2007):
* 1019-1031.
* - Zhou, Tao, Linyuan Lü, and Yi-Cheng Zhang. "Predicting missing links via local information."
* The European Physical Journal B 71.4 (2009): 623-630.
*
*
* @param the graph vertex type
* @param the graph edge type
*
* @author Dimitrios Michail
*/
public class ResourceAllocationIndexLinkPrediction
implements
LinkPredictionAlgorithm
{
private Graph graph;
/**
* Create a new prediction
*
* @param graph the input graph
*/
public ResourceAllocationIndexLinkPrediction(Graph graph)
{
this.graph = Objects.requireNonNull(graph);
}
@Override
public double predict(V u, V v)
{
List gu = Graphs.successorListOf(graph, u);
List gv = Graphs.successorListOf(graph, v);
Set intersection = new HashSet<>(gu);
intersection.retainAll(gv);
double result = 0d;
for (V z : intersection) {
int dz = graph.outDegreeOf(z);
if (dz == 0) {
throw new LinkPredictionIndexNotWellDefinedException(
"Index not well defined", Pair.of(u, v));
}
result += 1d / dz;
}
return result;
}
}