diff --git a/src/test/java/nearsoft/academy/bigdata/recommendation/MovieRecommender.java b/src/test/java/nearsoft/academy/bigdata/recommendation/MovieRecommender.java
new file mode 100644
index 0000000..7969dc3
--- /dev/null
+++ b/src/test/java/nearsoft/academy/bigdata/recommendation/MovieRecommender.java
@@ -0,0 +1,131 @@
+package nearsoft.academy.bigdata.recommendation;
+
+import java.io.BufferedReader;
+import java.io.BufferedWriter;
+import java.io.File;
+import java.io.FileInputStream;
+import java.io.FileReader;
+import java.io.FileWriter;
+import java.io.IOException;
+import java.io.InputStreamReader;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+import java.util.zip.GZIPInputStream;
+
+import org.apache.mahout.cf.taste.common.TasteException;
+import org.apache.mahout.cf.taste.impl.model.file.FileDataModel;
+import org.apache.mahout.cf.taste.impl.neighborhood.ThresholdUserNeighborhood;
+import org.apache.mahout.cf.taste.impl.recommender.GenericUserBasedRecommender;
+import org.apache.mahout.cf.taste.impl.similarity.PearsonCorrelationSimilarity;
+import org.apache.mahout.cf.taste.model.DataModel;
+import org.apache.mahout.cf.taste.neighborhood.UserNeighborhood;
+import org.apache.mahout.cf.taste.recommender.RecommendedItem;
+import org.apache.mahout.cf.taste.recommender.UserBasedRecommender;
+import org.apache.mahout.cf.taste.similarity.UserSimilarity;
+
+
+
+public class MovieRecommender{
+	private String file_s="";
+	private int dataProducts = 0;
+	private int dataUsers = 0;
+	private int dataReview = 0;	
+	HashMap<String, Integer> usersMap = new HashMap<String, Integer>();
+	HashMap<String, Integer> productsMap = new HashMap<String, Integer>();
+	private String Products = "";
+	private String Users = "";
+	private String Scores = "";
+
+	public MovieRecommender(String file_sile) throws IOException, NullPointerException {
+		this.file_s = file_sile;
+		this.dataReview = 0;
+		this.dataProducts = 0;
+		this.dataUsers = 0;
+		this.dataProcess();
+	}	
+
+	private void dataProcess() throws IOException {
+				
+        GZIPInputStream inGZIP = new GZIPInputStream(new FileInputStream(this.file_s));
+        BufferedReader bufferReader = new BufferedReader(new InputStreamReader(inGZIP));
+        String readingLine;
+
+        FileWriter fileWriter = new FileWriter(new File("movies_data.csv"));
+        BufferedWriter bufferedWriter = new BufferedWriter(fileWriter);
+        
+        Pattern productsPattern = Pattern.compile("product\\/productId: ([A-Z0-9]+)");
+        Pattern userPattern = Pattern.compile("review\\/userId: ([\\D\\d]+)");
+        Pattern scorePattern = Pattern.compile("review\\/score: ([0-9]+).([0-9]+)");
+        
+        Matcher matcherProduct, matcherUser, matcherScore;
+        
+        while((readingLine = bufferReader.readLine())!=null) {        	
+        	matcherProduct = productsPattern.matcher(readingLine);
+        	matcherUser = userPattern.matcher(readingLine);
+        	matcherScore = scorePattern.matcher(readingLine);
+        	if(matcherProduct.matches()) { Products = matcherProduct.group(1);        		
+        		if (!productsMap.containsKey(Products)) {
+        			dataProducts++;        			
+        			productsMap.put(Products, dataProducts);
+				}
+        	}else if (matcherUser.matches()) {
+        		dataReview++;
+        		Users = matcherUser.group(1);
+				if(!usersMap.containsKey(Users)) {
+					dataUsers++;
+					usersMap.put(Users, dataUsers);	
+				}
+				}else if (matcherScore.matches()) { Scores = matcherScore.group(1); }
+        	if (!Users.equals("") && (!Products.equals("") && (!Scores.equals(""))) ) {
+        		bufferedWriter.write(usersMap.get(Users) + "," + productsMap.get(Products) + "," + Scores + "\n");
+        		Users = "";
+			Products = "";
+			Scores = "";
+			}
+        }       
+        bufferedWriter.close();
+        fileWriter.close();
+        bufferReader.close();  
+	}
+	
+	public int getTotalReviews() {
+		return this.dataReview;
+	}
+	public int getTotalProducts() {
+		this.dataProducts = productsMap.size();
+		return this.dataProducts;
+	}
+	public int getTotalUsers() {
+		return this.dataUsers;
+	}
+	
+	private String getProductID(int value)
+        {
+        	for (String key : this.productsMap.keySet()) {
+            		if (productsMap.get(key)==value) {
+        	        return key;
+	        	}            
+        	}
+        return null;
+        }
+        
+	
+	public List<String> getRecommendationsForUser(String userID) throws IOException, TasteException, NullPointerException{
+		List<String> resultsList = new ArrayList<String>();
+		Integer userId = this.usersMap.get(userID);
+		DataModel model = new FileDataModel(new File("movies_data.csv"));
+
+        UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
+        UserNeighborhood neighborhood = new ThresholdUserNeighborhood(0.1, similarity, model);
+        UserBasedRecommender recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);
+        List<RecommendedItem> recommendations = recommender.recommend(userId, 3);
+        for (RecommendedItem recommendation : recommendations){
+            resultsList.add(getProductID(((int) recommendation.getItemID())));
+        }
+		return resultsList;
+	}
+}