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Second-hand recycling website developed in PHP provides precise recommendations for users
- WBOYOriginal
- 2023-07-02 13:09:06556browse
The second-hand recycling website developed by PHP provides accurate recommendations for users
As the resource environment worsens day by day, second-hand recycling becomes more and more important. Second-hand recycling websites have become a bridge connecting users and recyclers. In order to improve the user experience and allow users to find the products they need more conveniently and quickly, we can make precise recommendations to users through the second-hand recycling website developed in PHP.
1. Data preparation
Before development, product data needs to be prepared first. These product data may include product types, attributes, descriptions and other information. A database can be used to store this data, such as using a MySQL database. The following is an example of the structure of a simplified product data table:
CREATE TABLE `products` ( `id` int(11) NOT NULL AUTO_INCREMENT, `name` varchar(255) NOT NULL, `category` varchar(255) NOT NULL, `price` decimal(10,2) NOT NULL, `description` text NOT NULL, PRIMARY KEY (`id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
2. User personalized recommendations
Through the user’s browsing history, interests and hobbies and other information, we can generate a personalized recommendation for each user Recommended list. The following is an example of the structure of a simplified user data table:
CREATE TABLE `users` ( `id` int(11) NOT NULL AUTO_INCREMENT, `name` varchar(255) NOT NULL, `interests` text NOT NULL, `browse_history` text NOT NULL, PRIMARY KEY (`id`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
By analyzing the user's browsing history and interests, we can use PHP code to generate the user's personalized recommendation list. The following is a simplified code example:
<?php
// 获取用户浏览记录和兴趣爱好
$user_browse_history = $user['browse_history'];
$user_interests = $user['interests'];
// 查询数据库，获取匹配用户兴趣的商品列表
$sql = "SELECT * FROM `products` WHERE `category` IN ($user_interests)";
$result = mysqli_query($conn, $sql);
// 根据用户浏览记录，排除已经浏览过的商品
$exclude_product_ids = explode(',', $user_browse_history);
$recomend_products = [];
while ($row = mysqli_fetch_assoc($result)) {
if (!in_array($row['id'], $exclude_product_ids)) {
$recomend_products[] = $row;
}
}
// 输出推荐商品列表
foreach ($recomend_products as $product) {
echo $product['name'] . ' - ' . $product['price'] . '<br>';
}
?>The above example code is a simple process of user personalized recommendations. In practical applications, more accurate recommendations can also be made based on users' transaction records, reviews and other information.
3. Front-end display
Finally, we need to display these recommended products on the front-end page of the website so that users can see and interact with them. You can use HTML and CSS to build the front-end interface of the website, and use PHP code to dynamically insert recommended products into the page. The following is a sample code for a simplified front-end page:
<!DOCTYPE html>
<html>
<head>
<title>二手回收网站</title>
<style>
.product {
border: 1px solid #ccc;
padding: 10px;
margin-bottom: 10px;
}
</style>
</head>
<body>
<h1>个性化推荐</h1>
<!-- 动态插入推荐商品 -->
<?php foreach ($recomend_products as $product): ?>
<div class="product">
<h2><?php echo $product['name']; ?></h2>
<p><?php echo $product['description']; ?></p>
<p>价格：<?php echo $product['price']; ?></p>
</div>
<?php endforeach; ?>
</body>
</html>Through the above sample code, we can insert the user's personalized recommended product list into the front-end page of the website to achieve precise recommendations.
Summary
Through the second-hand recycling website developed through PHP, accurate recommendations for users can greatly improve the user experience and help users find the products they need more conveniently. By analyzing user data and querying the database, we can generate a personalized recommendation list and display it on the front-end page. The above example code is a simplified demonstration, and can be expanded and optimized according to specific needs in actual applications. I hope that the introduction of this article can help readers better understand and apply PHP to develop personalized recommendation functions in second-hand recycling websites.
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