Added MovieRecommender class

.gitignore

@@ -0,0 +1,4 @@
+.idea
+target/
+*.iml
+.DS_Store

pom.xml

@@ -26,5 +26,11 @@
           <version>4.7</version>
           <scope>test</scope>
       </dependency>
+      <dependency>
+          <groupId>org.slf4j</groupId>
+          <artifactId>slf4j-api</artifactId>
+          <version>1.7.5</version>
+      </dependency>
+
   </dependencies>
 </project>

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

@@ -0,0 +1,53 @@
+package nearsoft.academy.bigdata.recommendation;
+
+
+import com.google.common.collect.BiMap;
+import com.google.common.collect.HashBiMap;
+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.File;
+import java.io.IOException;
+import java.util.ArrayList;
+import java.util.List;
+
+public class BookRecommender {
+    List <String> RecommendedProducts ;
+    BiMap<String, Long> products ;
+    BiMap<String, Long> users ;
+
+    private String path;
+    public BookRecommender(String path, BiMap<String, Long> users, BiMap<String, Long> products)
+    {
+        this.RecommendedProducts = new ArrayList<String>();
+        this.path = path;
+        this.users = users;
+        this.products = products;
+    }
+
+    public List<String> getRecommendationsForUser( String userID) throws IOException, TasteException {
+        DataModel model = new FileDataModel(new File(this.path));
+        UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
+        UserNeighborhood neighborhood = new ThresholdUserNeighborhood(0.1, similarity, model);
+        UserBasedRecommender recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);
+        List <String> RecommendedProducts = new ArrayList<String>();
+        List<RecommendedItem> recommendations = recommender.recommend(this.users.get(userID),3);
+        for (RecommendedItem recomendation:recommendations)
+        {
+            long value = (long) recomendation.getItemID();
+            this.RecommendedProducts.add(this.products.inverse().get(value)  );
+        }
+
+        return this.RecommendedProducts;
+    }
+
+
+}

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

@@ -0,0 +1,82 @@
+package nearsoft.academy.bigdata.recommendation;
+import java.io.*;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.zip.GZIPInputStream;
+import org.apache.mahout.cf.taste.common.TasteException;
+import com.google.common.collect.BiMap;
+import com.google.common.collect.HashBiMap;
+
+public class MovieRecommender {
+    private String path;
+    int information;
+
+    BiMap<String, Long> products ;
+    BiMap<String, Long> users ;
+    long totalReviews = 0;
+    PrintWriter csvWriter ;
+    String product;
+    String user;
+
+    public static void main(String[] args) throws IOException, TasteException {
+
+    }
+    public MovieRecommender(String path) throws IOException, TasteException {
+        this.path = path;
+        this.totalReviews = 0;
+        this.information = 0;
+        this.users = HashBiMap.create();
+        this.products = HashBiMap.create();
+        this.csvWriter= new PrintWriter("dataset.csv");
+        BufferedReader reader;
+        InputStream stream = new GZIPInputStream(new FileInputStream(path));
+        reader = new BufferedReader(new InputStreamReader(stream, "US-ASCII"));
+        String line = reader.readLine();
+        long productID = 0;
+        long userID = 0;
+        while (line != null ) {
+            if (line.startsWith("product/productId:")) {
+                product = line.split(": ")[1];
+                if (!products.containsKey(product)) {
+                    products.put(product, productID);
+                    productID++;
+                }
+
+            }else if (line.startsWith("review/userId:")) {
+                user= line.split(": ")[1];
+                if (!users.containsKey(user)) {
+                    users.put(user, userID);
+                    userID++;
+                }
+
+            }else if (line.startsWith("review/score:")) {
+                this.totalReviews ++;
+                csvWriter.println(users.get(user) + "," + products.get(product) + "," + line.split(": ")[1]);
+
+            }
+            line = reader.readLine();
+        }
+        csvWriter.close();
+    }
+
+    public long getTotalReviews() {
+        return this.totalReviews;
+    }
+
+    public long getTotalProducts() {
+        return this.products.size();
+    }
+
+    public long getTotalUsers() {
+        return this.users.size();
+    }
+
+    public List<String> getRecommendationsForUser(String userID) throws IOException,TasteException {
+        BookRecommender bookRecommender = new BookRecommender("dataset.csv", this.users, this.products);
+
+        List <String> RecommendedProducts = new ArrayList<String>();
+        RecommendedProducts = bookRecommender.getRecommendationsForUser(userID);
+
+        return RecommendedProducts;
+    }
+}

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("/Users/sandraherrera/Downloads/movies.txt.gz");
         assertEquals(7911684, recommender.getTotalReviews());
         assertEquals(253059, recommender.getTotalProducts());
         assertEquals(889176, recommender.getTotalUsers());
@@ -24,7 +24,6 @@ public void testDataInfo() throws IOException, TasteException {
         assertThat(recommendations, hasItem("B0002O7Y8U"));
         assertThat(recommendations, hasItem("B00004CQTF"));
         assertThat(recommendations, hasItem("B000063W82"));
-
     }
 
 }