Improved Association Rule Mining based on UP-Growth Algorithm

Mining of associations have been considered from different point of views, the use of high-dimensional data sets could still be a hard process. Besides, one should considers that, regardless the heuristic considered to solve the problem, the number of data accesses is high, so a data structure that speeds up the queries is the keystone. In this regard, the goal is to propose a suitable data structure that enables to both handle and fast compute high-dimensional data sets. For that purpose, the desired data structure should allow either to simplify or to reorganize data items in order to reduce the data size and provide a faster access to the stored information. In this paper we introduce new algorithm known as UP-growth which has the ability to mine the high dimensional data in less time complexity.