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Copy pathRootedPageRankLinkPredictor.cpp
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55 lines (47 loc) · 2.29 KB
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/*
------------------------------------------------
Copyright (C) 2010 by Ryan N. Lichtenwalter
Email: rlichtenwalter@gmail.com
This file is part of LPmade.
LPmade is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. LPmade is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with LPmade. If not, see <http://www.gnu.org/licenses/>.
------------------------------------------------
*/
#include "RootedPageRankLinkPredictor.h"
#include "../Statistics.h"
#include <algorithm>
#include <tuple>
RootedPageRankLinkPredictor::RootedPageRankLinkPredictor( const WeightedNetwork& network, const WeightedNetwork& completeNetwork,double alpha ) : LinkPredictor(network,completeNetwork), alpha(alpha) {
}
RootedPageRankLinkPredictor::~RootedPageRankLinkPredictor() {
}
double RootedPageRankLinkPredictor::generateScore( unsigned int vertex, unsigned int neighbor ) {
if( this->vertex != vertex ) {
this->vertex = vertex;
this->scores = vector<double>( this->network.vertexCount() );
vector<double> oldPageRanks = vector<double>( this->network.vertexCount() );
vertex_t currentVertex = vertex;
this->scores.at( currentVertex )++;
for( unsigned int step = 1; true; step++ ) {
const neighbor_set_t& neighbors = this->network.outNeighbors( currentVertex );
if( neighbors.size() < 1 || (double)rand()/RAND_MAX < this->alpha ) {
currentVertex = vertex;
} else {
vertex_t randomNeighbor = rand() % neighbors.size();
currentVertex = neighbors.at( randomNeighbor ).first;
}
this->scores.at( currentVertex )++;
if( step == 100000 ) {
oldPageRanks = this->scores;
} else if( step % 100000 == 0 ) {
double r = Statistics<double>::sampleCorrelationCoefficient( oldPageRanks, this->scores );
// cerr << r << "\n";
if( r > 0.9999 ) {
return this->scores.at( neighbor );
} else {
oldPageRanks = this->scores;
}
}
}
}
return this->scores.at( neighbor );
}