Exploration In Commercial Websites On The Association Rules Base On The Consumers’ Behavior

The contemporary society, as the information technology constantly to mature, all kinds of enterprises and organizations are beginning to use the most advanced information technology for his own enterprise operation service, the use of the commercial style of EB is the best way to demonstrate this phenomenon.In many of the information technology, based on the Internet data mining of association rules become a hot research object.In the Internet environment, the network contains enormous data, in which a large number of valuable knowledge is hidden, it need people to discover.This era is known as information explosion which is the matter that each business should to confront.If businesses are able to correctly use the Internet data, the enterprise can rapid develop through the valuable information,and, conversely, a large number of redundant data may be the burden of enterprise.Data mining the valuable association rules from the mass Internet date has the significant value for the businesses.Researching in mining association rules of customers’ behavior in commercial websites is very important in terms of the method of data mining association rules. Owing to that, in ordinary operation, method of association rules mining only contain the purchase data for which customers left, but the data of customers’ browsing, selecting and assessing has be neglect in FP-Growth algorithm. So it may lead FP-Growth algorithm no longer in force.This thesis suggest a new way, which try to integrate commodity data with users action data in terms of association rules mining and, the users action will be divided in browsing, selecting, purchasing and assessing in this new method. Thus the association rules which it will supply may close to the real.