学习 API 示例

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;

/**
* This is a sample implementation of the learning optimizer.
* The interface ILearning may be found in the interact.jar library.
*
* To actually use this implementation, select ExternalLearning as the optimizationType in the offerServing node
* of the Interact application within the Platform configuration. Within the offerserving node there is also
* an External Learning config category - within there you must set the name of the class to this:
* com.unicacorp.interact.samples.learning.v2.SampleLearning. Please note however, this implementation is just a sample
* and was not designed to be used in a production environment.
*
*
* This example keeps track of accept and contact counts and uses the ratio of accept to contacts
* for a particular offer as the acceptance probability rate for the offer.
*
*
* Offers not presented will get higher priority for recommending.
* Offers with at least one contact will be ordered based on descending acceptance probability rate.
*
* Note: all counts are kept in memory. This is not a realistic scenario since you would run out of memory sooner or
* later. In a real production scenario, the counts should be persisted into a database.
*
*/

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);

}
}

}