## A survey of itemset mining

- Philippe Fournier-Viger, Chun-Wei Lin, Bay Vo, Tin C. Truong, Ji Zhang, Hoai Bac Le
- Wiley Interdisc. Rew.: Data Mining and Knowledge…
- 2017

- Published 2016 in HAIS

High-utility itemset mining is the task of finding the sets of items that yield a high utility (e.g. profit) in quantitative transaction databases. An important limitation of previous work on high-utility itemset mining is that utility is generally used as the sole criterion for assessing the interestingness of patterns. This leads to finding many itemsets that have a high profit but contain items that are weakly correlated. To address this issue, this paper proposes to integrate the concept of correlation in high-utility itemset mining to find profitable itemsets that are highly correlated, using the bond measure. An efficient algorithm named FCHM (Fast Correlated high-utility itemset Miner) is proposed to efficiently discover correlated high-utility itemsets. Experimental results show that FCHM is highly-efficient and can prune a huge amount of weakly correlated HUIs.

@inproceedings{FournierViger2016MiningCH,
title={Mining Correlated High-Utility Itemsets Using the Bond Measure},
author={Philippe Fournier-Viger and Chun-Wei Lin and Tai Dinh and Hoai Bac Le},
booktitle={HAIS},
year={2016}
}