/*
* Seldon -- open source prediction engine
* =======================================
* Copyright 2011-2015 Seldon Technologies Ltd and Rummble Ltd (http://www.seldon.io/)
*
**********************************************************************************************
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
**********************************************************************************************
*/
package io.seldon.recommendation;
import io.seldon.clustering.recommender.BaseItemCategoryRecommender;
import io.seldon.clustering.recommender.ItemRecommendationAlgorithm;
import io.seldon.clustering.recommender.ItemRecommendationResultSet;
import io.seldon.clustering.recommender.RecommendationContext;
import io.seldon.general.ItemStorage;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Set;
import org.apache.commons.lang.StringUtils;
import org.apache.log4j.Logger;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
/**
* @author firemanphil
* Date: 22/02/15
* Time: 11:50
*/
@Component
public class RecentCategoryItemsRecommender extends BaseItemCategoryRecommender implements ItemRecommendationAlgorithm {
private static final String name = RecentCategoryItemsRecommender.class.getSimpleName();
private static Logger logger = Logger.getLogger(RecentCategoryItemsRecommender.class.getName());
private final ItemStorage itemStorage;
@Autowired
public RecentCategoryItemsRecommender(ItemStorage itemStorage){
this.itemStorage = itemStorage;
}
@Override
public ItemRecommendationResultSet recommend(String client, Long user, Set<Integer> dimensions, int maxRecsCount, RecommendationContext ctxt, List<Long> recentItemInteractions) {
HashMap<Long, Double> recommendations = new HashMap<>();
Set<Long> exclusions;
if(ctxt.getMode() == RecommendationContext.MODE.INCLUSION){
logger.warn("Can't run RecentICategorytemsRecommender in inclusion context mode");
return new ItemRecommendationResultSet(name);
} else {
exclusions = ctxt.getContextItems();
}
Integer dimId = getDimensionForAttrName(ctxt.getCurrentItem(),client,ctxt);
if (dimId != null)
{
Collection<Long> recList = itemStorage.retrieveRecentlyAddedItemsTwoDimensions(client,maxRecsCount+exclusions.size(),dimensions,dimId).getItems();
if (recList.size() > 0)
{
double scoreIncr = 1.0/(double)recList.size();
int count = 0;
for(Long item : recList)
{
if (count >= maxRecsCount)
break;
else if (!exclusions.contains(item))
recommendations.put(item, 1.0 - (count++ * scoreIncr));
}
List<ItemRecommendationResultSet.ItemRecommendationResult> results = new ArrayList<>();
for (Map.Entry<Long, Double> entry : recommendations.entrySet()){
results.add(new ItemRecommendationResultSet.ItemRecommendationResult(entry.getKey(), entry.getValue().floatValue()));
}
if (logger.isDebugEnabled())
logger.debug("Recent items algorithm returned "+recommendations.size()+" items");
return new ItemRecommendationResultSet(results, name);
}
else
{
logger.warn("No items returned for recent items of dimension " + StringUtils.join(dimensions, ",") + " for " + client);
}
}
else
logger.info("Can't get dimension for item "+ctxt.getCurrentItem());
return new ItemRecommendationResultSet(Collections.EMPTY_LIST, name);
}
@Override
public String name() {
return name;
}
}