Research And Implementation Of Recommendation Mode In Agricultural Product Mall System Based On Data Mining

E-commerce as an important product of the information age, is still developing rapidly, and the E-commerce is one of the most dynamic areas of the information age also bring great convenience. However, with the development of E-commerce, it becomes more and more difficult for people to find their favorite commodities from the dazzling array of goods. In recent years, the recommendation system in E-commerce solved this problem to some extent. Recommendation system by collecting user data, analyze the user's hobbies, and then recommend to the user some goods that the user may be interested. However, the current E-commerce recommendation system in the recommended efficiency and recommended quality still has room for improvement. Our Advanced Network Management laboratory research and development of the "one village one product" agricultural mall system is a typical E-commerce site,with the continuous improvement of system functions and the increase in the number of goods, there is an urgent need to add recommendation function.Based on this, this paper mainly studies the collaborative filtering algorithm in the recommendation system and the recommendation mode in the agricultural product mall system.In this paper, firstly studying the collaborative filtering technology and content-based recommendation technology commonly used in data mining and recommendation systems. Then, a collaborative filtering recommendation algorithm based on item is put forward. After considering the important influence of the time characteristic on the recommendation result, an improved item-based collaborative filtering recommendation algorithm was proposed. The improved algorithm can make up for the shortcomings of the traditional item-based collaborative filtering recommendation algorithm, which does not consider the time characteristic, and improves the accuracy of the recommendation result.Then, by analyzing the specific recommendation requirements of the agricultural mall system, an integrated recommendation model for the system is designed, which can take corresponding recommendation strategies for different users' state, and further completes the architecture design of the recommended module of the system. Finally, the improved algorithm proposed in this paper and the design of the overall hybrid recommendation model applied to the agricultural mall system, then realized the recommended system function of the agricultural products mall system, and through the experimental verification of the recommended module good recommendation effect.