Research on Horizontal Optimization and Search Strategy for the Mining of Association Rules Based on TreeProject

The TreeProject algorithm is the most efficient solution to the problem that can be described as “the algorithm will not run if the dataset is very large”, but there are redundant projects in this algorithm In order to remove the redundant projects, the horizontal optimizing strategies are presented which consist of the combining strategy used in the mining process and the generating strategy used at the end of mining The advantages of this algorithm not only can reduce the search space and the memory requirements of the TreeProject algorithm, but also promote the mining of frequency items Furthermore, the judgment of the horizontal redundancy can be simplified from the two project databases into the two corresponding sets of transaction number, which can save the time, and can also improve the project operation without adding extra time From the time complexity and the space complexity, the HOP TreeProject algorithm based on this horizontal optimizing strategies greatly improves the TreeProject algorithm The experimental results also demonstrate the correctness of the above conclusions