Research On Cross-border E-commerce Customer Relationship Based On Rough Set

In the current Internet business,logistics between countries and cross-border payments under the background of rapid development,our country and related to agricultural products trade between the countries in behavior from large to small is achieved,by mass turned into miniaturization,large transaction amount into smaller orders,shorter cycle by long,trade pattern changes from low to high frequency.Many agricultural trade enterprises have developed from traditional foreign trade market to cross-border e-commerce market.Therefore,the rapid development of cross-border platforms promotes the development of small and micro agricultural enterprises and individual businesses,and brings unprecedented development opportunities for agricultural enterprises,merchants and farmers.In the era of Internet eruption,there is a large amount of customer data,complicated data structure,and easy to miss.With the introduction of rough set theory and the gradual development of singular value decomposition(SVD),the two theories are very effective in customer data mining and filling.Based on rough set theory and singular value analysis method,this paper carries out relevant research on customer management of cross-border e-commerce agricultural products.The main contents are as follows:1.By studying the basic theory of rough set and analyzing the necessity and advantages of customer relationship management in cross-border e-commerce,the classification index system of cross-border e-commerce customers of agricultural products is constructed according to the characteristics of the current customer classification of cross-border e-commerce customers of agricultural products and the selection principle of the customer index system of cross-border e-commerce customers of agricultural products.The index system is constructed according to purchase behavior,loyalty,credit and consumption preference.The distinction function is used to reduce the attributes of cross-border e-commerce customers.2.Based on the basic idea of ANALYTIC Hierarchy Process(AHP)AHP model,the customer classification evaluation index system and the solving steps of AHP are integrated to establish an information system for the customer data of Hunan Nianyanyouyu Import and Export Co.,LTD.,which is an agricultural cross-border e-commerce enterprise in Hunan,and calculate attribute weights.And analyzed that for the agricultural cross-border e-commerce enterprise,customer order times and total consumption are its important customer indicators.3.Analyzed the role of SVD collaborative filtering recommendation algorithm in customer relationship data of cross-border e-commerce,made tables of commodities that customers were interested in using SVD,and further divided the value of agricultural products customers according to the weight of each evaluation index calculated and the AHP model.Finally,a customer recommendation system suitable for hunan Niannianniyouyu Import and Export Co.,LTD.Through experimental verification,the model in this paper makes full use of rough set theory,the basic idea of AHP model and SVD algorithm,and realizes the establishment of customer classification and recommendation system for this cross-border agricultural e-commerce enterprise in Hunan province,which provides a very important theoretical and technical reference for the operation and development of cross-border e-commerce enterprises...