es.uam.eps.ir.relison.diffusion.selections.LimitedCountThresholdSelectionMechanism Maven / Gradle / Ivy
/*
* Copyright (C) 2020 Information Retrieval Group at Universidad Autónoma
* de Madrid, http://ir.ii.uam.es
*
* This Source Code Form is subject to the terms of the Mozilla Public
* License, v. 2.0. If a copy of the MPL was not distributed with this
* file, You can obtain one at http://mozilla.org/MPL/2.0/.
*/
package es.uam.eps.ir.relison.diffusion.selections;
import es.uam.eps.ir.relison.diffusion.data.Data;
import es.uam.eps.ir.relison.diffusion.data.PropagatedInformation;
import es.uam.eps.ir.relison.diffusion.simulation.SimulationState;
import es.uam.eps.ir.relison.diffusion.simulation.UserState;
import es.uam.eps.ir.relison.graph.edges.EdgeOrientation;
import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;
/**
* Selection mechanism that only propagates those received pieces which have been received (at least) a fixed
* number of times. It propagates any information piece that the user has received, from, at least, a
* given proportion of his neighbors.
*
*
* Reference: D. Kempe, J. Kleinberg, and E. Tardos. Maximizing the spread of influence through a social network, KDD 2003, pp. 137–146 (2003).
*
*
* It fixes the (maximum) number of received pieces to propagate.
*
* @author Javier Sanz-Cruzado ([email protected])
* @author Pablo Castells ([email protected])
*
* @param type of the users.
* @param type of the information pieces.
* @param type of the parameters.
*/
public class LimitedCountThresholdSelectionMechanism extends CountSelectionMechanism
{
/**
* Number of users that transmit an information piece before a user chooses to share it.
*/
private final int threshold;
/**
* Orientation for selecting the neighborhood.
*/
private final EdgeOrientation orientation;
/**
* Constructor.
* @param numOwn number of own pieces to propagate.
* @param numRec maximum number of received pieces to propagate.
* @param threshold number of users that transmit an information piece before a user chooses to share it.
* @param orientation orientation for selecting the number of neighbors to consider.
*/
public LimitedCountThresholdSelectionMechanism(int numOwn, int numRec, int threshold, EdgeOrientation orientation)
{
super(numOwn, numRec);
this.threshold = threshold;
this.orientation = orientation;
}
/**
*
* @param numOwn number of own pieces to propagate.
* @param numRec maximum number of received pieces to propagate.
* @param threshold number of users that transmit an information piece before a user chooses to share it.
* @param orientation orientation for selecting the number of neighbors to consider.
* @param numRepr number of pieces to repropagate.
*/
public LimitedCountThresholdSelectionMechanism(int numOwn, int numRec, int threshold, EdgeOrientation orientation, int numRepr)
{
super(numOwn, numRec, numRepr);
this.threshold = threshold;
this.orientation = orientation;
}
@Override
protected List getReceivedInformation(UserState user, Data data, SimulationState state, int numIter, Long timestamp)
{
// We first obtain al the possible information to repropagate:
int userId = data.getUserIndex().object2idx(user.getUserId());
List aux = new ArrayList<>();
// Select the pieces to propagate.
user.getReceivedInformation().forEach(info ->
{
if(info.getTimes() >= this.threshold)
{
aux.add(new PropagatedInformation(info.getInfoId(), numIter, userId));
}
});
// We do randomly select the information pieces to propagate among the ones received earlier.
return this.getPropagatedInformation(userId, this.getNumReceived(), numIter, aux);
}
}