An Improved Method for Frequent Itemset Mining
Anitha Modi, Radhika Krishnan · 2013
Abstract — Frequent itemset mining is an important step in association rule mining. Several algorithms have been proposed for efficient frequent itemset mining in transactional database. We present an improved approach to mine frequent itemset in transactional database. The algorithm idea is derived from two popular existing algorithms Apriori and FP-Growth. With reduced number of scans and improved intermediate steps the algorithm efficiency is improved.