## 1 Introduction  
With the exponential growth of Internet technology, e-commerce platforms have emerged as a fundamental component of the modern business landscape [1], establishing themselves as the dominant channel for consumer transactions. This digital transformation has profoundly revolutionized the conventional distribution paradigm of minor agricultural products. The increasing integration of agricultural commodities into digital marketplaces through e-commerce platforms has given rise to a novel distribution model: rural e-commerce. Functioning as an innovative distribution channel within the agricultural industry chain, rural e-commerce platforms have become instrumental in driving the comprehensive transformation of the agricultural value chain, enhancing industry development standards, and accelerating agricultural modernization processes. The digital transformation of agricultural product distribution is evidenced by the substantial and consistent growth in online retail sales of agricultural products in China. Official data from the Ministry of Commerce indicate a notable upward trajectory, with agricultural product e-commerce retail sales reaching CNY 486.7 billion in 2021, subsequently expanding to CNY 531.38 billion in 2022, and further growing to CNY 587.03 billion in 2023. This progressive annual increase reflects not merely quantitative market expansion but also signifies the deepening integration of digital technologies into traditional agricultural value chains. The consistent growth pattern demonstrates the resilience and increasing market penetration of agricultural e-commerce, suggesting a structural shift in consumer purchasing behavior toward digital channels for agricultural products. This evolution presents both significant opportunities and unique challenges for stakeholders across the agricultural sector, particularly regarding product recommendation systems that must effectively accommodate the distinctive characteristics of agricultural commodities within digital marketplaces. Rural e-commerce platforms serve as integrated hubs that connect various segments of the agricultural industry, encompassing production, processing, warehousing, and logistics, thereby establishing an efficient and streamlined marketplace for transactions between minor agricultural product suppliers (merchants) and consumers (users). However, these platforms face significant operational challenges due to the distinctive characteristics of minor agricultural product sales, particularly the pronounced seasonality in user demand and complex geographical distribution patterns. Previous research has demonstrated that the development of rural e-commerce is substantially influenced by multiple factors, including infrastructure conditions, individual characteristics, social networks, and resource endowments [2]. These multifaceted challenges have, to a considerable extent, impeded the broader adoption and advancement of rural e-commerce platforms. To address the fundamental challenges impeding the development of rural e-commerce, it is essential to conduct a comprehensive analysis of user-merchant transaction patterns on rural e-commerce platforms. [PERSON] [3] demonstrates that consumer behavior prediction and personalized recommendation generation can be effectively achieved through the integration of user-generated content analysis and sociological survey data. Following this methodology, deep mining of users' agricultural product consumption patterns enables the recommendation of products that not only align with individual preferences but also accommodate seasonal and regional characteristics, thereby facilitating precise minor agricultural product marketing and distribution. The implementation of such a system addresses an urgent need in rural e-commerce platforms and represents a critical factor in promoting the sustainable development of rural e-commerce ecosystems.