How to use PHP to implement real-time personalized recommendations of recommendation systems

How to use PHP to implement real-time personalized recommendations of recommendation systems

Recommendation systems have become an important part of many websites and applications. It can provide personalized recommended content based on users' interests and behavioral habits, improving user experience and the overall effect of the website. In this article, I will introduce how to implement a simple recommendation system using PHP and demonstrate how to make personalized recommendations in real time.

The basic principle of the recommendation system is to predict the content that the user may be interested in based on the user's historical behavior and the behavior of other users, and recommend these contents to the user. In order to achieve personalized recommendations, we need to collect user behavior data, such as the web pages the user browses, the buttons they click, etc. This data will be used to build a user interest model and make recommendations based on this model.

First, we need to create a database to store user behavior data. We will use MySQL as the database engine and create a table called "actions" to store user behavior data. The structure of the table is as follows:

CREATE TABLE actions (
    id INT AUTO_INCREMENT PRIMARY KEY,
    user_id INT,
    action VARCHAR(255),
    item_id INT,
    timestamp TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

Next, we need to write PHP code to capture the user's behavior and store it in the database. The following is a sample code for capturing the user's click behavior and storing it in the database:

<?php
// 连接数据库
$servername = "localhost";
$username = "username";
$password = "password";
$dbname = "database";

$conn = new mysqli($servername, $username, $password, $dbname);

// 捕获用户的点击行为
$action = "click";
$item_id = $_GET['item_id']; // 从GET请求中获取item_id
$user_id = $_SESSION['user_id']; // 从会话中获取user_id

// 将用户的行为存储到数据库中
$sql = "INSERT INTO actions (user_id, action, item_id) VALUES ('$user_id', '$action', '$item_id')";
$conn->query($sql);
$conn->close();
?>

In the above code, we first connect to the database through the mysqli class. We then get the user's click behavior and item_id from the GET request, and get the user's user_id from the session. Finally, we store the user's behavior in the database.

Next, we need to build a user interest model based on the user's behavioral data and make personalized recommendations based on the model. The following is a sample code for making recommendations based on the user's click behavior:

<?php
// 连接数据库
$servername = "localhost";
$username = "username";
$password = "password";
$dbname = "database";

$conn = new mysqli($servername, $username, $password, $dbname);

// 获取用户的兴趣模型
$user_id = $_SESSION['user_id']; // 从会话中获取user_id
$sql = "SELECT item_id FROM actions WHERE user_id = '$user_id' AND action = 'click'";
$result = $conn->query($sql);
$interests = array();

if ($result->num_rows > 0) {
    while ($row = $result->fetch_assoc()) {
        $item_id = $row['item_id'];
        $interests[] = $item_id;
    }
}

// 根据用户的兴趣模型进行推荐
$sql = "SELECT item_id FROM actions WHERE user_id <> '$user_id' AND action = 'click' AND item_id NOT IN (" . implode(',', $interests) . ")";
$result = $conn->query($sql);
$recommendations = array();

if ($result->num_rows > 0) {
    while ($row = $result->fetch_assoc()) {
        $item_id = $row['item_id'];
        $recommendations[] = $item_id;
    }
}

$conn->close();
?>

In the above code, we first obtain the user's user_id from the session, and obtain the user's click behavior from the database based on this user_id. Then, we store the item_id into the $interests array, representing the user's interest model. Next, we obtain the click behavior of other users from the database and filter out the item_id that the user has not clicked. Finally, we store the recommended item_id into the $recommendations array.

Finally, we need to display the recommended results to the user. The following is a simple sample code to display the recommended results:

<?php
foreach ($recommendations as $item_id) {
    // 根据item_id从数据库中获取item的详细信息
    $sql = "SELECT * FROM items WHERE item_id = '$item_id'";
    $result = $conn->query($sql);

    if ($result->num_rows > 0) {
        while ($row = $result->fetch_assoc()) {
            // 显示item的标题、图片等信息
            echo $row['title'] . "<br>";
            echo "<img src='" . $row['image'] . "'><br>";
            // ...
        }
    }
}
?>

In the above code, we use a foreach loop to traverse the $recommendations array and obtain item details from the database based on item_id. Then, we display the item’s title, picture and other information to the user.

To sum up, it is not complicated to use PHP to implement real-time personalized recommendations of the recommendation system. By collecting user behavior data, building a user interest model, and making personalized recommendations based on the model, we can provide better user experience and website effects. I hope this article will help you understand the implementation process of the recommendation system, and also provide you with some references in practical applications.

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