PHP Developer City, automatically recommends products collected by users

How to use PHP Developer City to realize the function of pushing users’ favorite products

In today’s e-commerce market, users’ personalized needs are becoming more and more important. In order to meet the personalized needs of users, the mall website not only needs to provide a diverse selection of products, but also needs to be able to accurately push products that match the user's interests based on the user's preferences and collection records. This article will introduce how to use PHP Developer City to realize the push function of users' favorite products.

1. Design database

First of all, we need to design a database to store user collection records and product information. We can create two tables: users and products.

1.1 users table

The users table is used to store user information, including fields such as user ID, user name, and password. The user ID is the primary key and is used to uniquely identify each user.

1.2 products table

The products table is used to store product information, including product ID, product name, product description, product image URL and other fields. The product ID is the primary key, used to uniquely identify each product.

In addition, we also need to create a favorites record table to store the user's favorite records. The favorites table includes two fields: user ID and product ID, which are used to record the user's favorite products.

2. Create a PHP page

Next, we need to create a PHP page to implement the function of pushing the user's favorite products. We can create two pages: login.php and index.php.

2.1 login.php page

login.php page is used for user login verification. The user needs to enter a username and password, and the system will verify whether the username and password entered by the user match the records in the database. If the verification passes, it jumps to the index.php page; if the verification fails, it returns to the login page.

In the login.php page, we can use PHP's mysqli library to connect to the database and write corresponding SQL statements to query user information and verify whether the user name and password entered by the user match.

2.2 index.php page

The index.php page is used to display the user’s favorite products and recommended products. The page can be divided into two parts: favorites list and recommendation list.

In the index.php page, we can use PHP's mysqli library to connect to the database and write corresponding SQL statements to query the user's favorite products and recommend other products that match the user's interests based on the user's interests.

In the collection list section, we can query the favorites table to obtain the user's favorite product information and display it on the page. At the same time, you can add the function of canceling favorites for each product. When the user clicks the cancel favorite button, the corresponding record in the favorites table can be deleted through SQL statements.

In the recommendation list section, we can recommend other products that match the user's interests based on the user's collection of products. You can query the products table and filter qualified product information by writing corresponding SQL statements, and then display them on the page. In order to improve the accuracy of recommendations, we can match based on the user's collection of product categories, product tags and other information.

3. Implement push function

In order to realize the push function of users’ favorite products, we can use PHP push service to push corresponding product information to users. You can use a third-party push service or use PHP's WebSocket to achieve real-time push.

In the index.php page, we can create a WebSocket connection after the user successfully logs in, and monitor changes in the user's favorite products in real time on the server side. When users add or delete favorite products, they can communicate with the server through WebSocket, and the server can push the corresponding products to the user in real time.

4. Optimize the recommendation algorithm

In order to improve the accuracy of recommendations, we can combine machine learning algorithms to optimize the recommendation algorithm. You can use PHP's machine learning library to build a recommendation model based on the user's collection records and browsing behavior, and predict the user's interests through the model.

By continuously iterating and optimizing the recommendation algorithm, the accuracy and user experience of pushing user favorites can be improved.

Summary:

This article introduces how to use the PHP Developer City to realize the push function of users' favorite products. By designing the database, creating PHP pages and implementing the push function, it is possible to display and push users' collections, and improve accuracy by optimizing the recommendation algorithm. This can improve the user's shopping experience and meet the user's personalized needs, thereby improving the mall's service quality and competitiveness.

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