Analysis of popular product recommendation strategies in malls developed using PHP

Analysis of recommendation strategies for popular products in malls developed using PHP

Abstract: With the rapid development of the Internet, e-commerce platforms are becoming more and more popular and concerned by people. In order to improve users' shopping experience and promote sales growth, malls need to use some recommendation algorithms to recommend popular products based on users' historical behaviors and personalized needs. This article will discuss the popular product recommendation strategy for the mall developed using PHP and give corresponding code examples.

1. User Behavior Data Collection
   In the mall, in order to recommend popular products to users, it is first necessary to collect user behavior data. Behavioral data includes users’ purchase history, browsing history, click records, etc. All user actions on the platform can be recorded and stored in the database for subsequent analysis and recommendations.

Code example:

// 用户购买商品
function buyProduct($userId, $productId) {
    // 将购买记录插入数据库
}

// 记录用户浏览商品
function browseProduct($userId, $productId) {
    // 将浏览记录插入数据库
}

// 记录用户点击商品
function clickProduct($userId, $productId) {
    // 将点击记录插入数据库
}

2. Recommendation algorithm selection
   The recommendation algorithm is the core of realizing popular product recommendation. Common recommendation algorithms include content-based recommendations, collaborative filtering recommendations, and deep learning recommendations. In the mall, in order to improve the recommendation effect of popular products, multiple recommendation algorithms can be used comprehensively.

Code example:

// 基于内容的推荐
function contentBasedRecommendation($userId) {
    // 根据用户的购买历史和浏览记录，推荐相似的商品
}

// 协同过滤推荐
function collaborativeFilteringRecommendation($userId) {
    // 根据用户的购买历史和其他用户的购买历史，推荐相似用户的喜好商品
}

// 深度学习推荐
function deepLearningRecommendation($userId) {
    // 使用深度学习模型，根据用户的行为数据进行商品推荐
}

3. Recommended result display
   The display of recommended results is an important part of the mall's recommendation of popular products. When displaying recommendation results, recommended products can be displayed to users in the form of lists, carousels, etc. based on the user's purchase intention and historical preferences.

Code example:

// 展示推荐结果
function showRecommendation($recommendations) {
    // 根据推荐结果，将商品以合适的形式展示给用户
}

In summary, the popular product recommendation strategy for the mall developed using PHP requires first collecting user behavior data, and then selecting the recommendation algorithm based on the collected data. and display of recommended results. This can improve the user's shopping experience and promote the mall's sales growth.

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