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Recommended product table design method for grocery shopping system in MySQL

Nov 01, 2023 am 11:49 AM
mysqlGrocery shopping systemRecommended product table design method

Recommended product table design method for grocery shopping system in MySQL

Recommended product table design method for food shopping system in MySQL

With the development of the Internet, more and more people choose to purchase food online. In order to improve users' shopping experience, many shopping platforms will recommend corresponding products based on users' purchase records and preferences. This article will introduce how to design the recommended product table of the grocery shopping system in MySQL, and provide specific code examples.

Before designing the recommended product list of the grocery shopping system, we first need to clarify some concepts and requirements. The function of the recommended product table is to recommend products that may be of interest to the user based on the user's purchase history and preferences. In order to implement this function, we need to create a recommended product table to store the associated information between users and products.

First, we can create a table named recommendation to store the association information between users and products. The fields of this table can include user ID (user_id) and product ID (product_id), and some other auxiliary fields can be added, such as recommendation time (recommend_time), etc.

CREATE TABLE recommendation (

id int NOT NULL AUTO_INCREMENT,
user_id int NOT NULL,
product_id int NOT NULL,
recommend_time datetime NOT NULL,
PRIMARY KEY (id),
INDEX user_id_index (user_id),
INDEX product_id_index (product_id)

);

User’s purchase records and preferences can be obtained through other tables, such as order table and user preference table. Here, we assume that there is already an order table named order, and the fields of the order table include order ID (order_id), user ID (user_id), product ID (product_id), etc.

CREATE TABLE order (

order_id int NOT NULL AUTO_INCREMENT,
user_id int NOT NULL,
product_id int NOT NULL,
order_time datetime NOT NULL,
PRIMARY KEY (order_id),
INDEX user_id_index (user_id),
INDEX product_id_index (product_id)

);

When a user places an order to purchase a product, we can insert the purchase record into the recommended product table through a trigger or stored procedure middle. The following is an example trigger for automatically inserting purchase records into the recommended products table when a user places an order.

DELIMITER //

CREATE TRIGGER after_insert_order
AFTER INSERT ON order
FOR EACH ROW
BEGIN

INSERT INTO recommendation (user_id, product_id, recommend_time)
VALUES (NEW.user_id, NEW.product_id, NOW());

END//

DELIMITER ;

Through the above trigger, when a new order is inserted into the order table, a new record will be inserted into the recommended product table accordingly.

In addition to recommending products based on the user's purchase history, we can also recommend products based on the user's preferences. Assume that there is already a user preference table named preference, which contains the user's preference rating for the product.

CREATE TABLE preference (

id int NOT NULL AUTO_INCREMENT,
user_id int NOT NULL,
product_id int NOT NULL,
rating int NOT NULL,
PRIMARY KEY (id),
INDEX user_id_index (user_id),
INDEX product_id_index (product_id)

);

In order to implement product recommendation based on user preferences, we can use a method based on collaborative filtering algorithm to insert into the recommended product table Related information between users. The following is an example stored procedure for inserting recommended product records based on associated information between users.

DELIMITER //

CREATE PROCEDURE generate_recommendation()
BEGIN

DECLARE i, j INT;
DECLARE user1_id, user2_id, product_id INT;
DECLARE similarity FLOAT;

-- 定义游标
DECLARE cur CURSOR FOR
    SELECT user_id, product_id FROM preference;
DECLARE CONTINUE HANDLER FOR NOT FOUND
    SET done = 1;

-- 循环遍历用户
OPEN cur;
read_loop: LOOP
    FETCH cur INTO user1_id, product_id;
    IF done THEN
        LEAVE read_loop;
    END IF;

    -- 查询与当前用户喜好相似的其他用户
    SELECT user_id, rating INTO user2_id, similarity
    FROM preference
    WHERE user_id != user1_id
    ORDER BY ABS(rating - (SELECT rating FROM preference WHERE user_id = user1_id))
    LIMIT 5;

    -- 插入推荐商品记录
    INSERT INTO recommendation (user_id, product_id, recommend_time)
    SELECT user2_id, product_id, NOW()
    FROM preference
    WHERE user_id = user1_id;

END LOOP;
CLOSE cur;

END//

DELIMITER ;

Through the above In the stored process, we can insert recommended product records based on the similarity of preferences between users. In this way, when the user queries recommended products, he only needs to obtain the corresponding records from the recommended product table.

To sum up, this article introduces the method of designing the recommended product table of the grocery shopping system in MySQL and provides specific code examples. By analyzing the user's purchase history and preferences, we can recommend products suitable for the user and improve the user's shopping experience. Of course, according to actual needs and specific application scenarios, we can make corresponding modifications and adjustments based on the above methods.

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