Research on Improved Algorithm Based on AprioriTid Transaction and Candidate Item Compression

Abstract

Association rule mining is one of the most popular technologies. This paper researches on AprioriTid of association rule mining technique, and concludes the two main problems in AprioriTid. One is giant candidate Tid list, the other one is the mount of nonsense projects storage. As to the main problems in AprioriTid Algorithm, this paper proposes an improved AprioriTid Algorithm based on transaction set compression and candidate item set compression. This algorithm optimizes the self-connection of frequent item set to reduce the candidate item set through deleting affairs and reducing data set; after testing and comparing the algorithm in many aspects by UCI standard test set, the improved algorithm grows by 10%-20% in time efficiency.