update v0.0.2

Author: tigoCaval

composer.json

@@ -6,6 +6,7 @@
        "recommendation",
        "collaborative filtering",
        "euclidean distance",
+       "slope one",
        "recommender system",
        "recommendation system",
        "recommendation algorithm",

src/Collaborative/SlopeOneCollaborative.php

@@ -0,0 +1,155 @@
+<?php
+namespace Tigo\Recommendation\Collaborative;
+
+use Tigo\Recommendation\Collaborative\Base;
+ 
+/**
+ * Slope One algorithm
+ * 
+ * @author Tiago A C Pereira <tiagocavalcante57@gmail.com>
+ */
+class SlopeOneCollaborative extends Base
+{
+      
+    /**
+     * Get average weight.
+     * @var array
+     */
+    protected $weight = [];
+      
+    /**
+     * Get items rated by other customers (difference matrix).
+     * @var array
+     */
+    protected $factor = [];
+
+    /**
+     * Get items rated by the client.
+     * @var array
+     */
+    protected $myProduct = [];
+
+     /**
+      * Get recommend. 
+      * @param array $table
+      * @param mixed $user
+      * @param mixed $score
+      * 
+      * @return array
+      */
+     public function recommend($table, $user, $score = 0)
+     {
+          return $this->filterRating($this->prediction($table, $user, $score));
+     }
+
+    /**
+     * Get customer rated product and update format.
+     * @param array $table
+     * @param mixed $user
+     * 
+     * @return array
+     */
+    private function update($table, $user)
+    {
+        $this->ratedProduct($table, $user);
+        foreach($this->product as $item){
+            $this->myProduct[$item[self::USER_ID]][$item[self::PRODUCT_ID]] = $item[self::SCORE];
+        }
+        foreach($this->other as $item){ 
+            $this->factor[$item[self::USER_ID]][$item[self::PRODUCT_ID]] = $item[self::SCORE]; 
+        }
+    }
+    
+    /**
+     * Get calculated items (f(x) = x + b).
+     * @param array $table
+     * @param mixed $user
+     * 
+     * @return array
+     */
+    private function calculateItems($table, $user)
+    {
+        $this->update($table, $user);
+        $diff = $this->factor;
+        $data = [];
+        foreach($this->factor as $key1 => $item1){
+            foreach($item1 as $key2 => $value1){ 
+                foreach($diff as $key3 => $item2){
+                    foreach($item2 as $key4 => $value2){
+                         if(!isset($data[$key2][$key4]) && !isset($this->weight[$key2][$key4])){
+                            $data[$key2][$key4] = 0;
+                            $this->weight[$key2][$key4] = 0; 
+                         }       
+                         if($key1 == $key3){
+                            $data[$key2][$key4] += ($value1 - $value2);
+                            $this->weight[$key2][$key4] += 1;
+                         }         
+                    }
+                }
+            }     
+        }
+        return $data; 
+    }
+
+    /**
+     * Get average difference.
+     * @param array $table
+     * @param mixed $user
+     * 
+     * @return array
+     */
+    private function averageDifference($table, $user)
+    {
+        $component = $this->calculateItems($table, $user);
+        $data = [];
+        foreach($this->myProduct as $key1 => $item1){
+            foreach($item1 as $key2 => $value1){
+               foreach($component as $key3 => $item2){
+                   foreach($item2 as $key4 => $value2){
+                        if($key2 == $key4){
+                            if(!isset($data[$key3][$key4]))
+                                $data[$key3][$key4] = 0;
+                            if($this->weight[$key3][$key4] > 0)    
+                                $data[$key3][$key4] +=  ($value2/$this->weight[$key3][$key4])+$value1;   
+                        }   
+                   }
+               }
+            }
+        }
+        return $data;
+    }
+
+    /**
+     * Get prediction.
+     * @param array $table
+     * @param mixed $user
+     * @param mixed $score
+     * 
+     * @return array
+     */
+    private function prediction($table, $user, $score)
+    {
+        $component = $this->averageDifference($table, $user);
+        $weight = [];
+        $data = [];
+        $result = [];
+        foreach($component as $key1 => $item1){
+            foreach($item1 as $key2 => $value1){
+                  if(!isset($weight[$key1]) && !isset($data[$key1]) ){
+                     $weight[$key1] = 0;
+                     $data[$key1] = 0;
+                  }   
+                  $weight[$key1] += $this->weight[$key1][$key2];
+                  $data[$key1] += $value1 * $this->weight[$key1][$key2];                
+            }
+        }
+        
+        foreach($data as $key1 => $value){
+            $average = round($value/$weight[$key1],2);
+            if($average >= $score)
+               $result[$key1] = $average;
+        }
+        return $result;
+    } 
+       
+}

src/Recommend.php

@@ -3,6 +3,7 @@
 
 use Tigo\Recommendation\Collaborative\EuclideanCollaborative;
 use Tigo\Recommendation\Collaborative\RankingCollaborative;
+use Tigo\Recommendation\Collaborative\SlopeOneCollaborative;
 use Tigo\Recommendation\Factories\CollaborativeFactory; 
 
 /**
@@ -46,5 +47,18 @@ public function euclidean($table, $user, $score = 0)
    { 
       return $this->method->doFactory(new EuclideanCollaborative(), $table, $user, $score);   
    }
-   
+
+   /**
+    * Get slope one | collaborative filtering algorithm.
+    * @param array $table
+    * @param mixed $user
+    * @param mixed $score
+    * 
+    * @return [type]
+    */
+   public function slopeOne($table, $user, $score = 0)
+   {
+      return $this->method->doFactory(new SlopeOneCollaborative(), $table, $user, $score);
+   }
+
 }

tests/RecommendTest.php

@@ -53,5 +53,12 @@ public function  testEuclideanExpectedResult()
             $this->assertEquals($luana, ['A'=>0.87,'G'=>1]);
       }
 
+      public function testSlopeOneExpectedResult()
+      {
+            $client = new Recommend();
+            $pedro = $client->slopeOne($this->table,'Pedro');
+            $this->assertEquals($pedro,['C'=>0.57]);
+      }
+
 
 }