Proficient Algorithms for Mining Elevated Service Item Sets Commencing Transactional Databases
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2015, Vol 4, Issue 4
Abstract
Association rule mining is used to stumble on the patronize item sets in substantial database. In the data mining field, utility mining materialize as an essential topic that to excavation the high value item sets from databases which consign to verdict the item sets with elevated profits. The vast number of high utility item sets formulate a challenging hitch for the mining accomplishment, awaited to generate more potential high utility item sets. So it expends higher progression in outsized database and diminute the mining efficiency. They proposed two novel approaches such as UP growth and UP-growth+ in addition to compact UP Tree data structure, which is used for well-organized discovering high utility item sets from huge transactional databases. In existing system indiscriminate memory allocation is used to squirrel away the candidate that conduct to high potential I/O operations. Also this method is time devour and requires high memory storage. In sequence to solve this problem in proposed system, we used taxonomy with R-hashing technique for the memory allocation. Hence the applicant items are stored with their particular memory in UP tree. The experimental result illustrates that the proposed system is additional successful than the existing techniques according to the memory space and the amount of candidate item sets initiation and input and output operations.
Authors and Affiliations
gunamani k, vishnumurthy s
Keywords
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