Abstract:In the real production and sales scenarios of agricultural products, the network structure formed by consumers co-purchase behavior is very complex and changeable. Although the community discovery algorithm can effectively dig out the hidden information behind the co-purchase behavior, there are problems that the analysis results are not easy to understand, and the supporting decision-making conditions are insufficient. Because of the widespread application of community discovery algorithms in the analysis of co-purchase networks, and the ability of visualization technology to present the analysis results, a visual analysis method for the co-purchase networks of agricultural products based on community discovery was proposed. Firstly, the method used the community discovery algorithm Clauset-Newman-Moore (CNM) to divide the agricultural product co-purchase network. Secondly, the quantity of agricultural products in different communities in the network structure, the frequency of co-purchase behaviors, and the proportion of the price mode of agricultural products were analyzed, and then interactive analysis on the information of customers who co-purchase a certain agricultural product in each community was conducted. Finally, the analysis results were displayed interactively and visually. According to the visual interface, some behavioral rules of co-purchases were obtained, and then their consumption rules were deeply explored. In order to better present the visual analysis method, a set of dynamic sales data of agricultural product in Qingdao area were interactively explored and analyzed through the design of a visual analysis interface, and the sales model found can not only inspire the improvement and optimization of the manufacturers marketing methods, but also can help consumers to better choose agricultural products that suit them.
