Bit Mask Search Algorithm for Trajectory Database Mining

Mining great service entities in trajectory database indicates to the exposure of entities with huge service like acquisition. The extensive number of contender entities degrades the mining achievement in terms of execution time and space stipulation. The position may become worse when the database consists of endless lengthy transactions or lengthy huge utility entity sets. In this paper, we use two algorithms, namely Utility Pattern Growth (UP –Growth) for mining huge utility entities with a set of adequate approaches for pruning contender entities. The previous algorithms do not contribute any compaction or compression mechanism the density in bit vector regions. To raise the density in bit-vector sector the Bit search Mask Search (BM