package com.rapidminer.ItemRecommendation;
import java.util.List;
import com.rapidminer.data.EntityMapping;
import com.rapidminer.data.IEntityMapping;
import com.rapidminer.data.IPosOnlyFeedback;
import com.rapidminer.data.PosOnlyFeedback;
import com.rapidminer.example.Attribute;
import com.rapidminer.example.AttributeRole;
import com.rapidminer.example.Attributes;
import com.rapidminer.example.Example;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.operator.Operator;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.UserError;
import com.rapidminer.operator.ports.InputPort;
import com.rapidminer.operator.ports.OutputPort;
import com.rapidminer.operator.ports.metadata.ExampleSetPassThroughRule;
import com.rapidminer.operator.ports.metadata.ExampleSetPrecondition;
import com.rapidminer.operator.ports.metadata.GenerateNewMDRule;
import com.rapidminer.operator.ports.metadata.MetaData;
import com.rapidminer.operator.ports.metadata.SetRelation;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.tools.Ontology;
/**
*Random item recommender
*
* @see com.rapidminer.ItemRecommendation.RandomO
* @see com.rapidminer.ItemRecommendation.Random
*
* @author Matej Mihelcic (Ru�er Bo�kovi� Institute)
*/
public class RandomO extends Operator {
private InputPort exampleSetInput = getInputPorts().createPort("example set");
private OutputPort exampleSetOutput1 = getOutputPorts().createPort("Model");
private OutputPort exampleSetOutput = getOutputPorts().createPort("example set");
public List<ParameterType> getParameterTypes() {
List<ParameterType> types = super.getParameterTypes();
return types;
}
/**
* Constructor
*/
public RandomO(OperatorDescription description) {
super(description);
exampleSetInput.addPrecondition(new ExampleSetPrecondition(exampleSetInput, "user identification", Ontology.ATTRIBUTE_VALUE));
exampleSetInput.addPrecondition(new ExampleSetPrecondition(exampleSetInput, "item identification", Ontology.ATTRIBUTE_VALUE));
getTransformer().addRule(new ExampleSetPassThroughRule(exampleSetInput, exampleSetOutput, SetRelation.EQUAL) {
});
getTransformer().addRule(new GenerateNewMDRule(exampleSetOutput1, new MetaData(ItemRecommender.class)) {
});
}
@Override
public void doWork() throws OperatorException {
ExampleSet exampleSet = exampleSetInput.getData();
IPosOnlyFeedback training_data=new PosOnlyFeedback();
IEntityMapping user_mapping=new EntityMapping();
IEntityMapping item_mapping=new EntityMapping();
if (exampleSet.getAttributes().getSpecial("user identification") == null) {
throw new UserError(this,105);
}
if (exampleSet.getAttributes().getSpecial("item identification") == null) {
throw new UserError(this, 105);
}
Attributes Att = exampleSet.getAttributes();
AttributeRole ur=Att.getRole("user identification");
Attribute u=ur.getAttribute();
AttributeRole ir=Att.getRole("item identification");
Attribute i=ir.getAttribute();
for (Example example : exampleSet) {
double j=example.getValue(u);
int uid=(int) j;
j=example.getValue(i);
int iid=(int) j;
training_data.Add(user_mapping.ToInternalID(uid), item_mapping.ToInternalID(iid));
checkForStop();
}
System.out.println(training_data.GetMaxItemID()+" "+training_data.GetMaxUserID());
Random recommendAlg=new Random();
recommendAlg.SetFeedback(training_data);
recommendAlg.user_mapping=user_mapping;
recommendAlg.item_mapping=item_mapping;
recommendAlg.Train();
exampleSetOutput.deliver(exampleSet);
exampleSetOutput1.deliver(recommendAlg);
}
}