An empirical evaluation of high utility itemset mining algorithms

C Zhang, G Almpanidis, W Wang, C Liu - Expert Systems with applications, 2018 - Elsevier
High utility itemset mining (HUIM) has emerged as an important research topic in data
mining, with applications to retail-market data analysis, stock market prediction, and …

[PDF][PDF] An empirical evaluation of high utility itemset mining algorithms

C Zhang, G Almpanidis, W Wang, C Liu - 2017 - researchgate.net
High utility itemset mining (HUIM) has emerged as an important research topic in data
mining, with applications to retail-market data analysis, stock market prediction, and …

[PDF][PDF] An empirical evaluation of high utility itemset mining algorithms

C Zhang, G Almpanidis, W Wang, C Liu - 2018 - philippe-fournier-viger.com
abstract High utility itemset mining (HUIM) has emerged as an important research topic in
data mining, with applications to retail-market data analysis, stock market prediction, and …

An empirical evaluation of high utility itemset mining algorithms

C Zhang, G Almpanidis, W Wang, C Liu - Expert Systems with …, 2018 - dl.acm.org
Running time and memory consumption comparison of 10 HUI mining algorithms.
Comparison tests using 9 real world and 72 synthetic datasets. d2HUP and EFIM are the top …

[PDF][PDF] An empirical evaluation of high utility itemset mining algorithms

C Zhang, G Almpanidis, W Wang, C Liu - 2018 - philippe-fournier-viger.com
abstract High utility itemset mining (HUIM) has emerged as an important research topic in
data mining, with applications to retail-market data analysis, stock market prediction, and …