Online Web mining transactions association rules using frame metadata model


Introduces a frame metadata model to facilitate the continuous association rules of Web transactions. A new set of association rules can be derived with the updating of the Web log file by the Web transactions in the frame metadata model. This 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 is invoked by an event attribute in the method class which computes the association rules continuously. The result is active Web mining that is capable of deriving association rules of Web transactions continuously or incrementally using the frame metadata model.



Software And Hardware

• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL