FP-Tree Improve Efficiency & Increase Scalability by Applying Parallel Projected

doi: 10.5138/bjdmn.v1i1.207

Abstract

FP-tree method is a efficient algorithm to mine frequent patterns, in spite of long or short frequent patterns. By using compact tree structure and partitioning-based, divide-and-conquer searching method, it reduces the search costs substantially. But just as the analysis multi-CPU to solve this problem. But these methods apparently increase the costs for exchanging and combining control information, and the algorithm complexity is also greatly increased, cannot solve this problem efficiently. Even if adopting multi-CPU technique, raising the requirement of hardware, the performance improvement is still limited. Is there any other way that one may reduce these costs in FP-tree construction, performance improvement is still limited.

Keywords: Partitioning-based, parallel, Projection, data mining, AI, Information.