Introduction to arules — Mining Association Rules and Frequent Item Sets

By Michael Hahsler, Bettina Gr, Kurt Hornik. 2006

60 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. P. H. Hu
2. Jing Gao
3. Qi He
4. Tsang-Hsiang Cheng
5. Ming Ni
6. Anqi Xu
7. Zhenhua Zhang
8. Yuanyuan Gao

Citations in the corpus

• Interpreting tree ensembles with inTrees (2014, background): “Association rule analysis [2,21] discovers associations between items in transaction data sets, where one transaction consists of one or multiple items.”
• A deep learning approach for detecting traffic accidents from social media data (2018, methodology): “The association rules can be unveiled by the Apriori algorithm (Agrawal and , 1994; Hahsler et al., 2007).”
• Incorporating association rule networks in feature category-weighted naive Bayes model to support weaning decision making (2017, background): “, Yes or No) on the right-hand side, then it evaluates and selects rules according to prespecified confidence and lift thresholds [21].”