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Large transactions take very long time to access the data and the system performance will be degraded and the speed will be reduced. In order to maintain large transactions in an easy and faster way a concept called slicing is used in this paper. Slicing is a process of grouping of two data into a single data in order to reduce the space and also to reduce the time taken to produce the data. The slicing uses two concepts as generalization and bucketization. Generalization is a process where the grouped data can be viewed separately if required in order to get a clear view of the data in the database. Bucketization is the process where the data are found with the help of the age perspective. The original data and the duplicate data are separated using this process. The slicing partitions the data both horizontally and vertically. The main advantage of the slicing is that it handles the high dimensional data.

MINING ELEVATED SERVICE ITEMSETS ON TRANSACTIONAL RECORDSETS USING SLICING