Exemple d'API d'apprentissage

package com.unicacorp.interact.samples.learning.v2;

import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

import com.unicacorp.interact.samples.learning.SampleOptimizer.MyOfferSorter;
import com.unicacorp.interact.treatment.optimization.IClientArgs;
import com.unicacorp.interact.treatment.optimization.IInteractSession;
import com.unicacorp.interact.treatment.optimization.ILearningConfig;
import com.unicacorp.interact.treatment.optimization.ILearningContext;
import com.unicacorp.interact.treatment.optimization.IOffer;
import com.unicacorp.interact.treatment.optimization.LearningException;
import com.unicacorp.interact.treatment.optimization.v2.ILearning;
import com.unicacorp.interact.treatment.optimization.v2.ITreatment;

/**
* Ceci est un exemple d'implémentation de l'optimiseur d'apprentissage.
* L'interface ILearning se trouve dans la bibliothèque interact.jar.
*
* Pour utiliser cette implémentation, sélectionnez ExternalLearning comme optimizationType dans le noeud offerServing
* de l'application Interact dans la configuration Platform. Le noeud offerserving comporte aussi
* une catégorie de configuration External Learning dans laquelle vous devez définir le nom de la classe comme suit :
* com.unicacorp.interact.samples.learning.v2.SampleLearning. Veuillez noter toutefois que cette implémentation est un simple exemple
* n'est pas conçue pour être utilisée dans un environnement de production.
*
*
* Cet exemple effectue le suivi des décomptes des acceptations et des contacts et utilise le ratio acceptations/contacts
* correspondant à une offre particulière pour calculer le taux de probabilité d'acceptation de l'offre.
*
*
* Les offres non présentées bénéficient d'une priorité de recommandation plus élevée.
* Les offres ayant au moins un contact doivent être classées en fonction du taux décroissant de probabilité d'acceptation.
*
* Remarque : tous les décomptes sont conservés en mémoire. Il ne s'agit pas d'un scénario réaliste car la mémoire sera insuffisante
* à un moment donné. Dans un scénario de production réel, les décomptes doivent être conservés dans une base de données.
*
*/

public class SampleLearning implements ILearning
{

// A map of offer ids to contact count for the offer id
private Map<Long,Integer> _offerToContactCount = new HashMap<Long, Integer>();

// A map of offer ids to contact count for the offer id
private Map<Long,Integer> _offerToAcceptCount = new HashMap<Long, Integer>();

/* (non-Javadoc)
* @see com.unicacorp.interact.treatment.optimization.v2.ILearning#initialize
* (com.unicacorp.interact.treatment.optimization.v2.ILearningConfig, boolean)
*/
public void initialize(ILearningConfig config, boolean debug) throws LearningException
{
// If any remote connections are required, this is a good place to initialize those connections as this
// method is called once at the start of the interact runtime webapp.
// This example does not have any remote connections and prints for debugging purposes that this method will
// be called
System.out.println("Calling initialize for SampleLearning");
}

/* (non-Javadoc)
* @see com.unicacorp.interact.treatment.optimization.v2.ILearning#reinitialize
* (com.unicacorp.interact.treatment.optimization.v2.ILearningConfig, boolean)
*/
public void reinitialize(ILearningConfig config, boolean debug) throws LearningException
{
// If an IC is deployed, this reinitialize method is called to allow the implementation to
// refresh any updated configuration settings
System.out.println("Calling reinitialize for SampleLearning");
}

/* (non-Javadoc)
* @see com.unicacorp.interact.treatment.optimization.v2.ILearning#logEvent
* (com.unicacorp.interact.treatment.optimization.v2.ILearningContext,
* com.unicacorp.interact.treatment.optimization.v2.IOffer,
* com.unicacorp.interact.treatment.optimization.v2.IClientArgs,
* com.unicacorp.interact.treatment.optimization.IInteractSession, boolean)
*/
public void logEvent(ILearningContext context, IOffer offer, IClientArgs clientArgs,
IInteractSession session, boolean debug) throws LearningException
{
System.out.println("Calling logEvent for SampleLearning");

if(context.getLearningContext()==ILearningContext.LOG_AS_CONTACT)
{
System.out.println("adding contact");

// Keep track of all contacts in memory
synchronized(_offerToAcceptCount)
{
Integer count = _offerToAcceptCount.get(offer.getOfferId());
if(count == null)
count = new Integer(1);
else
count++;
_offerToAcceptCount.put(offer.getOfferId(), ++count);
}

}
else if(context.getLearningContext()==ILearningContext.LOG_AS_ACCEPT)
{
System.out.println("adding accept");
// Keep track of all accept counts in memory by adding to the map
synchronized(_offerToAcceptCount)
{
Integer count = _offerToAcceptCount.get(offer.getOfferId());
if(count == null)
count = new Integer(1);
else
count++;
_offerToAcceptCount.put(offer.getOfferId(), ++count);
}
}

}

/* (non-Javadoc)
* @see com.unicacorp.interact.treatment.optimization.v2.ILearning#optimizeRecommendList
* (java.util.List, com.unicacorp.interact.treatment.optimization.v2.IClientArgs,
* com.unicacorp.interact.treatment.optimization.IInteractSession, boolean)
*/
public List<ITreatment> optimizeRecommendList(List<ITreatment> recList,
IClientArgs clientArgs, IInteractSession session, boolean debug)
throws LearningException
{
System.out.println("Calling optimizeRecommendList for SampleLearning");

// Sort the candidate treatments by calling the sorter defined in this class and return the sorted list
Collections.sort(recList,new MyOfferSorter());

// now just return what was asked for via "numberRequested" variable
List<ITreatment> result = new ArrayList<ITreatment>();

for(int x=0;x<(Integer)clientArgs.getValue(IClientArgs.NUMBER_OF_OFFERS_REQUESTED) && x<recList.size();x++)
{
result.add(recList.get(x));
}
return result;
}

/* (non-Javadoc)
* @see com.unicacorp.interact.treatment.optimization.v2.ILearning#shutdown
* (com.unicacorp.interact.treatment.optimization.v2.ILearningConfig, boolean)
*/
public void shutdown(ILearningConfig config, boolean debug) throws LearningException
{
// If any remote connections exist, this would be a good place to gracefully
// disconnect from them as this method is called at the shutdown of the Interact runtime
// webapp. For this example, there is nothing really to do
// except print out a statement for debugging.
System.out.println("Calling shutdown for SampleLearning");

}
// Sort by:
// 1. offers with zero contacts - for ties, order is based on original input
// 2. descending accept probability rate - for ties, order is based on original input

public class MyOfferSorter implements Comparator<ITreatment>
{
private static final long serialVersionUID = 1L;

/* (non-Javadoc)
* @see java.lang.Comparable#compareTo(java.lang.Object)
*/
public int compare(ITreatment treatment1, ITreatment treatment2)
{

// get contact count for both treatments
Integer contactCount1 = _offerToContactCount.get(treatment1.getOffer().getOfferId());
Integer contactCount2 = _offerToContactCount.get(treatment2.getOffer().getOfferId());

// if treatment hasn't been contacted, then that wins
if(contactCount1 == null || contactCount1 == 0)
return -1;

if(contactCount2 == null || contactCount2 == 0)
return 1;

// get accept counts
Integer acceptCount1 = _offerToAcceptCount.get(treatment1.getOffer().getOfferId());
Integer acceptCount2 = _offerToAcceptCount.get(treatment2.getOffer().getOfferId());

float acceptProbability1 = (float) acceptCount1 / (float) contactCount1;
float acceptProbability2 = (float) acceptCount2 / (float) contactCount2;

// descending order
return (int) (acceptProbability2 - acceptProbability1);

}
}

}