摘要
在实际的农产品生产销售场景中,消费者共同购买行为所形成的网络结构非常复杂且多变。虽然社区发现算法可以有效挖掘出共同购买行为背后隐藏的信息,但存在分析结果不易理解、支持决策条件不足的问题。为此,考虑到社区发现算法在共同购买网络分析中的广泛应用及可视化技术对分析结果的呈现能力,提出一种基于社区发现的共同购买网络可视化分析方法。该方法首先利用社区发现算法Clauset-Newman-Moore(CNM)划分共同购买网络,其次对网络结构的不同社区中农产品数量、共同购买行为频数和农产品价格众数所占百分比进行分析,然后对各社区共同购买农产品的消费者信息进行交互式分析,最后将分析结果进行交互式可视化展示,根据可视化界面得出共同购买的一些行为规律,进而深度挖掘消费者的消费模式。为了更好地呈现该分析方法,通过设计实现的可视化分析界面,交互式探索分析了一组在青岛地区的农产品动态销售数据。
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.
作者
孙瑞志
侯曼曼
赵凯艺
SUN Ruizhi;HOU Manman;ZHAO Kaiyi(College of Information and Electrical Engineering,China Agricultural University,Beijing 100083,China;Scientific Research Base for Integrated Technologies of Precision Agriculture(Animal Husbandry),Ministry of Agriculture and Rural Affairs,Beijing 100083,China)
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2021年第S01期482-488,共7页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家重点研发计划项目(2016YFB0501805)
综合数据服务系统之基础平台建设项目(JZNYYY001)
