@article{JSSv014i15, title={arules - A Computational Environment for Mining Association Rules and Frequent Item Sets}, volume={14}, url={https://www.jstatsoft.org/index.php/jss/article/view/v014i15}, doi={10.18637/jss.v014.i15}, abstract={Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases. The R package arules presented in this paper provides a basic infrastructure for creating and manipulating input data sets and for analyzing the resulting itemsets and rules. The package also includes interfaces to two fast mining algorithms, the popular C implementations of Apriori and Eclat by Christian Borgelt. These algorithms can be used to mine frequent itemsets, maximal frequent itemsets, closed frequent itemsets and association rules.}, number={15}, journal={Journal of Statistical Software}, author={Hahsler, Michael and Grün, Bettina and Hornik, Kurt}, year={2005}, pages={1–25} }