Online Web Mining Transactions Association Rules using Frame Metadata Model

1 This paper is funded by Strategic Research Grant 7000895 of City University of Hong Kong Abstract In this paper, we introduce a frame metadata model to facilitate the continuous association rules of web transactions. A new set of association rules can be derived with the update of the web log file by the web transactions in the frame metadata model. The frame metadata model consists of two types of classes: static classes and active classes. The static classes describe the web transactions of the association rule table. The active classes are event driven, obtaining web transactions when invoked by a certain event. Whenever an update occurs in the existing web transactions in the web log file, a corresponding update will be invoked by an event attribute in the method class which will compute the association rules continuously. The result is an active web mining capable of deriving association rules of a web transactions continuously or incrementally using frame metadata model.