From 08a7d348bc73bda2cb8d97929e7633db9c799163 Mon Sep 17 00:00:00 2001
From: Fernando Salcido <fsr313@gmail.com>
Date: Fri, 17 Apr 2020 23:48:30 -0700
Subject: [PATCH] agregando MovieRecommender

---
 .../recommendation/MovieRecommender.java      | 139 ++++++++++++++++++
 1 file changed, 139 insertions(+)
 create mode 100644 src/test/java/nearsoft/academy/bigdata/recommendation/MovieRecommender.java

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..1780ce2
--- /dev/null
+++ b/src/test/java/nearsoft/academy/bigdata/recommendation/MovieRecommender.java
@@ -0,0 +1,139 @@
+package nearsoft.academy.bigdata.recommendation;
+
+import java.io.BufferedReader;
+import java.io.File;
+import java.io.FileInputStream;
+//import java.io.FileReader;
+import java.io.FileWriter;
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.InputStreamReader;
+import java.util.ArrayList;
+//import java.util.HashMap;
+import java.util.List;
+//import java.util.Map;
+import java.util.zip.GZIPInputStream;
+
+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;
+
+
+public class MovieRecommender {
+    private String resource_path;
+    private int totalproducts;
+    private int totalreviews;
+    private int totalusers;
+    private BiMap<String,Integer> productHash;
+    private BiMap<String,Integer> usersHash;
+    public MovieRecommender(String resource_path)throws IOException{
+        this.resource_path = resource_path;
+        this.totalproducts = 0;
+        this.totalreviews = 0;
+        this.totalusers = 0; 
+        this.productHash = HashBiMap.create();
+        this.usersHash = HashBiMap.create();
+        readReviewsFile(resource_path);
+    }
+    /*
+        productId
+        UserId
+        profileName
+        helpfulness
+        score
+        time
+        summary
+        text:
+
+        productId
+    */
+    private void readReviewsFile(String path) throws IOException{
+        File result = new File("resultados.csv");
+        FileWriter fw = new FileWriter(result);
+        int current_user = 0;
+        int current_product = 0;
+        InputStream stream = new GZIPInputStream(new FileInputStream(path));
+        //BufferedReader br = new BufferedReader(new FileReader(path));
+        BufferedReader br = new BufferedReader(new InputStreamReader(stream));
+        String line;
+        
+
+        while((line = br.readLine()) != null){
+            if(line.startsWith("product/productId:")){
+                //System.out.println("hola mundo");
+                String product_id = line.split(" ")[1];
+                //System.out.println("xddd "+product_id);
+                //System.out.println("asdasd  "+ this.productHash.containsKey(product_id));
+                if(this.productHash.containsKey(product_id) != true){
+                    this.totalproducts++;
+                    this.productHash.put(product_id, this.totalproducts);
+                    current_product = this.totalproducts;
+                }else{
+                    current_product = this.productHash.get(product_id);
+                }
+                continue;
+            }
+            if(line.startsWith("review/userId")){
+                String user_id = line.split(" ")[1];
+                if(!this.usersHash.containsKey(user_id)){
+                    this.totalusers++;
+                    this.usersHash.put(user_id,this.totalusers);
+                    current_user = this.totalusers;
+                }else{
+                    current_user = this.usersHash.get(user_id);
+                }
+            }
+            if(line.startsWith("review/score")){
+                String score = line.split(" ")[1];
+                fw.write(current_user+","+current_product+","+score+"\n");
+                this.totalreviews++;
+            }
+        }
+        fw.close();
+        br.close();
+
+        //B003AI2VGA
+    }
+
+
+
+
+	public int getTotalReviews() {
+		return totalreviews;
+	}
+	public int getTotalProducts() {
+		return totalproducts;
+	}
+	public int getTotalUsers() {
+		return totalusers;
+	}
+	public List<String> getRecommendationsForUser(String user) throws IOException,TasteException {
+		DataModel model = new FileDataModel(new File("resultados.csv"));
+        UserSimilarity similarity = new PearsonCorrelationSimilarity(model);
+        UserNeighborhood neighborhood = new ThresholdUserNeighborhood(0.1, similarity, model);
+        UserBasedRecommender recommender = new GenericUserBasedRecommender(model, neighborhood, similarity);
+
+        int user_id = this.usersHash.get(user);
+
+        List<RecommendedItem> recommendations = recommender.recommend(user_id,3);
+
+        List<String> recommendationsString = new ArrayList<String>();
+        
+        BiMap<Integer, String> product_hash_inverse = this.productHash.inverse();
+
+        for(RecommendedItem recommendation: recommendations){
+            recommendationsString.add(product_hash_inverse.get((int)recommendation.getItemID()));
+        }
+        return recommendationsString;        
+	}
+}