POM, MovieRecommender

pom.xml

@@ -12,6 +12,8 @@
 
   <properties>
     <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+      <maven.compiler.source>1.8</maven.compiler.source>
+      <maven.compiler.target>1.8</maven.compiler.target>
   </properties>
 
   <dependencies>

src/test/java/nearsoft/academy/bigdata/recommendation/MovieRecommender.java

@@ -0,0 +1,145 @@
+package nearsoft.academy.bigdata.recommendation;
+
+
+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;
+
+
+import java.io.*;
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+
+public class MovieRecommender {
+    String path;
+    int repMovies,repUsers;
+    int user,product,review;
+    HashMap<String, Integer> userId = new HashMap<String, Integer>();
+    HashMap<String, Integer> products = new HashMap<String, Integer>();
+    HashMap<Integer,String> productId = new HashMap<Integer,String>();
+
+    public MovieRecommender(String pathUrl) throws IOException {
+        this.path = pathUrl;
+        convert();
+    }
+
+    public void convert() throws IOException {
+        this.user=0;
+        this.product=0;
+        this.review=0;
+        this.repMovies=0;
+        this.repUsers=0;
+        String idUser="",idProduct="", scoreReview="";
+
+        BufferedReader reader = new BufferedReader(new FileReader(path));
+        String line;
+
+        String uRegex = "review\\/userId: ([\\D\\d]+)";
+        String pRegex = "product\\/productId: ([\\D\\d]+)";
+        String rRegex = "review\\/score: ([\\D\\d]+)";
+
+        Pattern userPattern = Pattern.compile(uRegex);
+        Pattern productPattern = Pattern.compile(pRegex);
+        Pattern reviewPattern = Pattern.compile(rRegex);
+
+
+        FileWriter csvWriter = new FileWriter("list.csv");
+
+        Matcher matcher;
+
+        boolean match;
+
+        line= reader.readLine();
+
+        while (line != null){
+
+            matcher = productPattern.matcher(line);
+            match = matcher.matches();
+
+            if (match){
+                String[] parts = line.split(": ",2);
+                idProduct= parts[1];
+                if(products.containsKey(idProduct))
+                    this.repMovies++;
+                else{
+                    this.product++;
+                    products.put(idProduct,this.product);
+                    productId.put(this.product,idProduct);
+                }
+
+            }
+
+            matcher = userPattern.matcher(line);
+            match = matcher.matches();
+
+            if (match){
+                String[] parts = line.split(": ",2);
+                idUser= parts[1];
+                if(userId.containsKey(idUser))
+                    this.repUsers++;
+                else{
+                    this.user++;
+                    userId.put(idUser,this.user);
+                }
+
+            }
+
+            matcher = reviewPattern.matcher(line);
+            match = matcher.matches();
+
+            if (match){
+                String[] parts = line.split(": ",2);
+                scoreReview= parts[1];
+                this.review++;
+            }
+
+            if(idProduct != "" && idUser != "" && scoreReview != "") {
+               csvWriter.append(userId.get(idUser).toString());
+               csvWriter.append(",");
+                csvWriter.append(products.get(idProduct).toString());
+                csvWriter.append(",");
+                csvWriter.append(scoreReview);
+                csvWriter.append("\n");
+               idUser="";
+               idProduct="";
+               scoreReview="";
+            }
+            line=reader.readLine();
+
+        }
+        csvWriter.flush();
+        csvWriter.close();
+        reader.close();
+
+    }
+
+    public int getTotalReviews(){ return  this.review; }
+    public int getTotalProducts(){ return this.product; }
+    public int getTotalUsers(){ return  this.user; }
+
+    public List <String> getRecommendationsForUser(String id) throws IOException, TasteException {
+        DataModel model = new FileDataModel(new File("list.csv"));
+        UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
+        UserNeighborhood neighborhood = new ThresholdUserNeighborhood(0.1, similarity, model);
+        UserBasedRecommender recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);
+
+        List<String> recommendations = new ArrayList<String>();
+
+        for (RecommendedItem recommendation : recommender.recommend(userId.get(id), 3)) {
+            recommendations.add(productId.get((int)(recommendation.getItemID())));
+        }
+
+        return recommendations;
+    }
+
+}

src/test/java/nearsoft/academy/bigdata/recommendation/MovieRecommenderTest.java

@@ -15,7 +15,7 @@ public class MovieRecommenderTest {
     public void testDataInfo() throws IOException, TasteException {
         //download movies.txt.gz from 
         //    http://snap.stanford.edu/data/web-Movies.html
-        MovieRecommender recommender = new MovieRecommender("/path/to/movies.txt.gz");
+        MovieRecommender recommender = new MovieRecommender("movies.txt");
         assertEquals(7911684, recommender.getTotalReviews());
         assertEquals(253059, recommender.getTotalProducts());
         assertEquals(889176, recommender.getTotalUsers());