@article{55ffde336d9642d3a0b6d6865786fe3c,
title = "arules - A computational environment for mining association rules and frequent item sets",
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. (authors' abstract)",
author = "Michael Hahsler and Bettina Gr{\"u}n and Kurt Hornik",
note = "Updated version",
year = "2005",
doi = "10.18637/jss.v014.i15",
language = "English",
volume = "14",
pages = "1 -- 25",
journal = "Journal of Statistical Software",
issn = "1548-7660",
publisher = "University of California at Los Angeles",
number = "15",
}