es.uam.eps.ir.relison.diffusion.selections.PureRecommenderSelectionMechanism 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.SimulationEdgeTypes;
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.HashSet;
import java.util.List;
/**
* Selects information pieces to propagate depending on the original users and whether they have been propagated through
* recommended links. A user can only propagate an information piece owned by another user if it comes from one of such
* links.
*
* @author Javier Sanz-Cruzado ([email protected])
* @author Pablo Castells ([email protected])
*
* @param type of the users.
* @param type of the information.
* @param type of the parameters.
*/
public class PureRecommenderSelectionMechanism extends CountSelectionMechanism
{
/**
* Neighborhood the information pieces come from. In case of IN, information comes from the followers of the users. In case of OUT (usual)
* from the followees. Finally, in case of UND, from any of them.
*/
private final EdgeOrientation orientation;
/**
* Constructor.
* @param numOwn number of own information pieces to propagate for each user and iteration.
* @param numPropagate number of received information to propagate for each user and iteration.
* @param orientation neighborhood the information pieces come from
*/
public PureRecommenderSelectionMechanism(int numOwn, int numPropagate, EdgeOrientation orientation)
{
super(numOwn, numPropagate);
this.orientation = orientation;
}
/**
* Constructor.
* @param numOwn number of own information pieces to propagate for each user and iteration.
* @param numPropagate number of received information to propagate for each user and iteration.
* @param numRepr number of propagated information pieces to propagate for each user and iteration.
* @param orientation neighborhood the information pieces come from
*/
public PureRecommenderSelectionMechanism(int numOwn, int numPropagate, int numRepr, EdgeOrientation orientation)
{
super(numOwn, numPropagate, numRepr);
this.orientation = orientation;
}
@Override
protected List getReceivedInformation(UserState user, Data data, SimulationState state, int numIter, Long timestamp)
{
List receivedToPropagate = new ArrayList<>();
List fromRec = new ArrayList<>();
HashSet setInfo = new HashSet<>();
U u = user.getUserId();
int userId = data.getUserIndex().object2idx(u);
user.getReceivedInformation().forEach(info ->
{
List creators = new ArrayList<>(info.getCreators());
for (Integer creator : creators)
{
if (creator != null)
{
U creatorUser = data.getUserIndex().idx2object(creator);
boolean rec = false;
if (this.orientation == EdgeOrientation.IN)
{
if (data.getGraph().getEdgeType(creatorUser, u) == SimulationEdgeTypes.RECOMMEND)
rec = true;
}
else if (this.orientation == EdgeOrientation.OUT)
{
if (data.getGraph().getEdgeType(u, creatorUser) == SimulationEdgeTypes.RECOMMEND)
rec = true;
}
else
{
if (data.getGraph().containsEdge(u, creatorUser))
rec = data.getGraph().getEdgeType(u, creatorUser) == SimulationEdgeTypes.RECOMMEND;
if (data.getGraph().containsEdge(creatorUser, u))
rec = rec || (data.getGraph().getEdgeType(creatorUser, u) == SimulationEdgeTypes.RECOMMEND);
}
if (rec)
fromRec.add(info);
}
}
});
return this.getPropagatedInformation(userId, this.getNumReceived(), numIter, fromRec);
}
}