Quality Depth-First Closed Itemsets (DCI_Closure) Associator

The objective of this thesis work is to design an efficient Data Mining algorithm to extract the data efficiently from the transactional database. There are different algorithms available to mine the data from databases. We propose a new Data Mining Algorithm named DCI_CLOSURE ALGORITHM using Association rules for discovering closed frequent Itemsets. DCI_CLOSURE Algorithm is an extension of DCI_CLOSED Algorithm with Association Rules, Efficient Lattices and Hash Map. This algorithm adopts several optimization techniques to save the storage space as well as extraction time in computing itemset closures and their support value. The proposed algorithm, which unlike other previous proposals does not scan the whole data set. We are going to eliminate single Itemsets by the purpose we need only pair of items so we reduce the single itemset and calculate number of itemset through the formula 2n-(n+1).