摘要
By applying the approaches of Data Mining into the Electronic Commerce, the owner of the Electronic Commerce can find out the really useful knowledge from the mass of data to make a right decision. Association rules mining has be used in order to find out the user access pattern in Electronic Commerce. Since it can not really fit in the Web log mining, the traditional association rules mining must be improved. Based on the traditional association rules mining algorithm, a new frequent path algorithm is proposed. It gets the transaction database using maxim forward segmentation algorithm and gets all the frequent paths that satisfy minimum support and minimum confidence in the transaction database. The new algorithm can help the owner of Electronic Commerce to improve the Web site designing.
- 出版日期2009
- 单位武汉工程大学