Association Rule Mining Using New FP-Linked List Algorithm
Sohrabi Mohammad Karim, Hasannejad Marzooni Hamidreza · Journal of advances in computer research · 2016
Finding frequent patterns plays a key role in exploring association patterns, correlation, and many other interesting relationships that are applicable in TDB. Several association rule mining algorithms such as Apriori, FP have been proposed in the literature. FP structure from transaction database and recursively traverse this tree to extract frequent patterns which satisfies the minimum support manner. Because of its high effici algorithms have used FP patterns. These algorithms change the FP this paper, we propose a new frequent pattern Growth idea which is using a frequent patterns. The bit matrix transforms the dataset and prepares it to construct as a linked list which is used by our new FPBitLink Algorithm study and experimental results algorithms.