In this paper, the weight of the incremental mining thinking optimization algorithm, for users to recommend personalized product configuration provides an effective solution. The method is mainly divided into three parts, first using the platform to build up user tracking module for tracking user behavior and collecting data; then combined with the user's behavior recently, the use of association rules mining based on the weight increment Apriori algorithm; final complete the product according to the recommended procedure to dig out results. By mining algorithm optimization, greatly improving the efficiency and accuracy of the product is recommended with the change in user behavior and changes in the system, more in line with the actual situation. Experimental results show that the algorithm can effectively solve the problem of product recommendation, compared to the traditional association rule mining algorithm, the accuracy is improved by 4%.