The document discusses the Apriori algorithm and modifications using hashing and graph-based approaches for mining association rules from transactional datasets. The Apriori algorithm uses multiple passes over the data to count support for candidate itemsets and prune unpromising candidates. Hashing maps itemsets to integers for efficient counting of support. The graph-based approach builds a tree structure linking frequent itemsets. Both modifications aim to improve efficiency over the original Apriori algorithm. The document also notes challenges in designing perfect hash functions for this application.