A Survey of Distributed Association Rule Mining Algorithms

Association Rule Mining is a popular and well researched method for discovering interesting relations between variables in large databases. It is intended to identify strong rules discovered in databases using different measures of interestingness. Most ARM algorithms focus on a sequential or centralized environment where no external communication is required. Distributed ARM algorithms, aim to generate rules from different data sets spread over various geographical sites; hence, they require external communications throughout the entire process. Distributed ARM is one of the major research fields of Data Mining (DM). DARM algorithm efficiency is highly dependent on data distribution. The paper reviews different algorithms developed for DARM and also discusses the different ways in which data is distributed. Agents are software entities developed to make distributed computing more efficient. They have also been used in Data Mining. The paper discusses the role of agents in DARM.