Research on Consumers Consumption Behavior Based on Ant System
with the market competition being increasingly intensive, it is necessary for company to carry out one-to-one marketing to consumers. Therefore, the ability to predict consumers consumption behavior basing on data mining has become a key source of competitive advantage for company. In this paper, we propose a novel algorithm, which bases on ant colony optimization (ACO) to cluster consumers consumption data sets with different favor for predicting consumers behavior. The algorithm is applied to grouping consumer data into classes or clusters for revealing consumers consumption behavior. The novel algorithm adopts simulated annealing concept for ants to decreasingly visit cities to get local optimal solutions. Finally, the algorithm is validated by the example of clustering consumers credit card data. The result indicates the algorithm is successful in clustering data for analyzing consumers behavior. The research presented in this paper makes contribution to predicting consumers consumption behavior.
consumer consumption behavior ant system clustering data mining
Chong Wang Yanqing Wang
Business School, 2.Library Huaihai Institute of Technology Lianyungang, 222000, China School of Management Harbin Institute of Technology Harbin, 150001,China
国际会议
上海
英文
1210-1214
2011-07-26（万方平台首次上网日期，不代表论文的发表时间）