The Application Of Data Mining Based On Association Rules In C Company's Export Full Container

Database technology has been widely popularized and used since 1980s. With the expansion of the database capacity, especially some new data source has been more and more popularized such as Data Warehouse and Web. The main problem that people face is no longer lacking of adequate information for using but how to use the data effectually in the ocean data. Meeting this challenge, data mining comes into being. Data Mining is the information processing technology, which is developing very fast in recent years. Using data mining, people can abstract information and knowledge from a great deal of data which is incomplete noisy dark and random. The information and knowledge we got was ignored and had not been known before potentially useful.Association rules mining is an important sub-branch of data mining which mines interesting association or correlation relationships among a large set of data items. Association rules are considered interesting if they satisfy both a minimum support threshold and a minimum confidence threshold. Association rules mining has become a hot research topic in recent years, and it has been used widely in elective marketing, decision analysis ,business management and so on.In this paper ,we first explained the concept of Data Mining and its application in logistics, then introduces the algorithm: Apriori. An overview on the famous algorithm Apriori, its advantages and weakness are pointed out. We introuduce other two algorithms which can avoid the weakness of Apriori. At last we apply this data mining method that based on association rules to the export full container, and analyze the mining result, propose instructive opinion.