How to use PHP to implement the popular product recommendation function of the mall

With the rapid development of e-commerce, more companies are beginning to choose to conduct business online. For a shopping mall website, the product recommendation function is very important because it can help companies promote sales and improve customer satisfaction. In this article, we will introduce how to use PHP to implement the popular product recommendation function of the mall.

1. Collect data

To implement the popular product recommendation function, we need to collect some data on the website. The focus is to collect information such as purchase volume, number of visits, product classification, etc. The purchase volume can be obtained through the order database, the visit volume can be obtained through logs, and the product classification can be obtained through the classification data table. We need to summarize this data in a table to facilitate analysis of the recommendation algorithm.

2. Select the recommendation algorithm

The recommendation algorithm is the key to realizing the popular product recommendation function. The algorithm based on collaborative filtering is a commonly used recommendation algorithm. It can predict the products that the user may purchase by analyzing the user's historical shopping behavior. At the same time, we can also combine product attributes, product evaluation and other factors to achieve more accurate recommendation functions.

3. Write the recommendation algorithm code

After selecting the recommendation algorithm, we need to use PHP to write the code for the recommendation algorithm. Specifically, we need to write a function that inputs the product ID and outputs a list of recommended products. The implementation process of this function is not complicated, and its main process is as follows:

1. Get user information. We need to obtain the ID of the logged-in user through session or cookie to facilitate calculation of the recommendation algorithm.
2. Query product information. Query the attributes and category information of the product based on the product ID.
3. Calculate user interest. Calculate the user's interest value in the product based on the user's historical shopping records and product attribute information.
4. Find neighbors. By calculating the similarity between users, we find several users that are most similar to the current user.
5. Recommended products. Based on the historical shopping records of neighbor users, the recommendation degree of the current product is calculated and sorted from high to low according to the recommendation degree.

4. Optimizing the recommendation algorithm

After completing the basic implementation of the recommendation algorithm, we need to consider some optimization strategies to improve the accuracy and efficiency of the recommendation algorithm. Specifically, we can consider the following aspects:

1. Add new products. There is no historical purchase data for new products. How to implement the recommendation function? You can use the popular ranking method, that is, to rank new products based on their visits and use them as one of the recommended products.
2. Consider product attributes. Product attributes have a great impact on recommendation algorithms. Keywords can be extracted from user reviews and matched based on product attributes to improve recommendation accuracy.
3. Using image recognition. For some products with special appearance or logo, image recognition technology can be used to identify the products and make recommendations.
4. Use caching technology. The recommendation algorithm requires a large amount of calculation, and caching methods such as redis can be used to cache the calculated results to improve efficiency.

5. Summary

Implementing the popular product recommendation function can not only increase the sales of the mall, but also improve the customer’s purchasing experience and satisfaction, which is conducive to the long-term development of the mall website. . During the implementation process, we need to pay attention to data collection and analysis, select suitable recommendation algorithms, and optimize strategies to improve accuracy and efficiency.

The above is the detailed content of How to use PHP to implement the popular product recommendation function of the mall. For more information, please follow other related articles on the PHP Chinese website!