协同过滤推荐系统。使用协同过滤的推荐算法。主题：排序算法，欧氏距离算法，斜率一算法.zip

# Recommendation algorithm Collaborative filtering recommendation system - Ranking algorithm using likes / dislikes or star-based rating - This package can be used in any PHP application or with any framework. - Download package: ```composer require tigo/recommendation``` - MIT license. ***Feel free to use this project***. ***Leave a star :star: or make a fork !*** *If you found this project useful, consider making a donation to support the developer.* [](https://www.paypal.com/donate?hosted_button_id=S7FBV5N6ZTRXQ) | [](https://www.paypal.com/donate?hosted_button_id=PPDESEV98R8KS) [](https://github.com/tigoCaval/recommendation-algorithm) ### Getting started Starting with composer 1. Install composer 2. Download package: ```composer require tigo/recommendation``` 3. PHP >= 7.0; Versions that have been tested: 7.2.25, 7.3.23 e 8.0.1. ```php //Somewhere in your project, you may need to use autoload include __DIR__ ."/vendor/autoload.php"; ``` ### Algorithms - ranking - euclidean - slope one ### Introduction Recommend a product using collaborative filtering ```php /** $table gets the array from the database. $user is the foreign key that represents the user who will receive the recommendation. **/ use Tigo\Recommendation\Recommend; // import class $client = new Recommend(); $client->ranking($table,$user); //optional third parameter refers to the score not accepted $client->euclidean($table,$user); //optional third parameter refers to the minimum accepted score $client->slopeOne($table, $user); //optional third parameter refers to the minimum accepted score ``` ### Configuration Sometimes, it may be necessary to rename the value of the constants (According to your database table). [](https://github.com/tigoCaval/recommendation-algorithm) - Configure: standard key (Directory: ```./src/configuration/StandardKey.php```) ```php const SCORE = 'score'; //score const PRODUCT_ID = 'product_id'; //Foreign key const USER_ID = 'user_id'; //Foreign key ``` ### Example A simple didactic demonstration of the algorithm ```php /** Example using "rating: liked and disliked" like: score = 1; dislike: score = 0 **/ $table = [ ['product_id'=> 'A', 'score'=> 1, 'user_id'=> 'Pedro' ], ['product_id'=> 'B', 'score'=> 1, 'user_id'=> 'Pedro' ], ['product_id'=> 'A', 'score'=> 1, 'user_id'=> 'João' ], ['product_id'=> 'B', 'score'=> 1, 'user_id'=> 'João' ], ['product_id'=> 'C', 'score'=> 1, 'user_id'=> 'João' ] ]; use Tigo\Recommendation\Recommend; // import class $client = new Recommend(); print_r($client->ranking($table,"Pedro")); // result = ['C' => 2] print_r($client->ranking($table,"Pedro",1)); // result = []; print_r($client->euclidean($table,"Pedro")); // result = ['C' => 1] print_r($client->euclidean($table,"Pedro", 2)); // result = [] ; print_r($client->slopeOne($table,'Pedro')); // result = ['C' => 1] print_r($client->slopeOne($table,'Pedro', 2)); // result = [] ``` ### Supporting this project If you are interested in supporting this project, you can help in many ways. Leave a star :star: or make a donation of any value. ### Sponsor supporting this project - [] ### Contributors - [Tiago A C Pereira](https://github.com/tigoCaval) - [list of contributors](https://github.com/tigoCaval/recommendation-algorithm/graphs/contributors) ### License MIT license. See the archive [License](https://github.com/tigoCaval/recommendation-algorithm/blob/main/LICENSE) ---