Memory Management by Using Association Rules Mining and Mine Frequent Pattern in Large Data Base

Association rules mining Rely on special data structures for the database in the primary memory. These data structure resides in the main memory, but these to handle the storage problem when they go out of the primary memory.VMM stores the overload data into the secondary memory based on some pre assumed memory handling method. So, it will arise the thrashing. This problem is solved by using ARM model capable of mining a transactional data base regardless of its size. The proposed data structure is constructed in the available allocated primary memory first. If it is grows out of the allocated memory quato them it forced to the secondary memory. The secondary memory version of the structure is accessed in a block-by-block basis so that both the spatial and temporal localities of the I/O access are optimized. the proposed framework takes control of the virtual memory access and hence manages the required virtual memory in an optimal way to the best benefit of the mining process to be served. Several clever data structures are used to facilitate these optimizations. Main purpose of this paper is to allocate memory and control this memory managing with the algorithm support.