High Performance Bit Search Mining Technique

Searching algorithms are closely related to the concept of dictionaries. String searching algorithms are too complex in all sorts of applications. To analyze an algorithm is to determine the amount of resources (such as time and storage) necessary to execute it. Most algorithms are designed to work with inputs of arbitrary length. Usually the efficiency or running time of an algorithm is stated as a function relating the input length to the number of steps (time complexity) or storage locations (space complexity). Time efficiency estimates depend on what defined to be all step. For the analysis to correspond usefully to the actual execution time, the time required to perform a step must be guaranteed to be bounded above by a constant. The main objective of this paper is to reduce the scanning the dataset by introducing new searching technique. So far, arrays, trees, hashing, depth first, breadth first, prefix tree based searching are used in association rule mining algorithms. If the size of the input is large, run time analysis of the algorithm is also increased. In this paper, a novel data structure is introduced so that it reduced dataset scan to one search. This new search technique is bit search. This bit search technique is to find the k itemsets (where k =1,2,3,......n) in one search scan.