An Efficient Algorithm for Incremental Mining of Association Rule Chin-Chen Chang, Yu-Chiang Li, and Jung-San Lee   View Paper (PDF)   Return to Fundamental Data Mining Algorithms Abstract Incremental algorithms can manipulate the results of earlier mining to derive the final mining output in various businesses. This study proposes a new algorithm, called the New Fast UPdate algorithm (NFUP) for efficiently incrementally mining association rules from a large transaction database. NFUP is a backward method that only requires scanning incremental database. Rather than rescanning the original database for some new generated frequent itemsets in the incremental database, we accumulate the occurrence counts of newly generated frequent itemsets and delete infrequent itemsets obviously. Thus, NFUP need not rescan the original database and to discover newly generated frequent itemsets. NFUP has good scalability in our simulation. ©2006 Association for Computing Machinery