Apriori, A Depth First Implementation

We will discuss , the depth first implementation of APRIORI as devised in 1999 (see [8]). Given a database, this algorithm builds a trie in memory that contains all frequent itemsets, i.e., all sets that are contained in at least minsup transactions from the original database. Here minsup is a threshold value given in advance. In the trie, that is constructed by adding one item at a time, every path corresponds to a unique frequent itemset. We describe the algorithm in detail, derive theoretical formulas, and provide experiments.

• Type: Conference
• Year: 2003
• Where: FIMI
• Authors: Walter A. Kosters, Wim Pijls
• Keywords: Data Mining, Depth first Implementation, FIMI 2003, Frequent Itemset, Unique Frequent Itemset