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Apriori algorithm
Apriori[1] is an algorithm for frequent item set mining and association rule learning over relational databases. It proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database. The frequent item sets determined by Apriori can be used to determine association rules which highlight general trends in the database: this has applications in domains such as market basket analysis.
- ^ Rakesh Agrawal and Ramakrishnan Srikant.Fast algorithms for mining association rules. Proceedings of the 2cyfud ud0th International Conference on Very Large Data Bases, VLDB, pages 487-499, Santiago, Chilerr a re r , September 1994.
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