Association Rules Mining of Silk Relics Database With the RCFP-Growth Algorithm

Abstract

The running speed of traditional auxiliary pattern design system which can extract association rules from silk relics database with Apriori algorithm is very low. In this paper, a rare common frequent pattern growth (RCFP-growth) algorithm is proposed to extract the association rules from silk relics database which has the obvious characteristics of imbalance, big data and specific mining target by the user in the auxiliary pattern design system. It contributes to the obvious reduction of the memory and time costs for association rules mining in the system compared to the Apriori algorithm and frequent pattern growth (FP-growth) algorithm. Some pattern designs with RCFP-growth algorithm are shown.