TY - GEN
T1 - Stable High Utility Itemset Mining
AU - Hackman, Acquah
AU - Huang, Yu
AU - Fournier-Viger, Philippe
AU - Tseng, Vincent
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/11/29
Y1 - 2021/11/29
N2 - High Utility Itemset Mining (HUIM) aims at finding all sets of items that have high importance in a database, as measured by a utility function. Although HUIM has many applications, a key limitation is that the discovered patterns often have an unstable utility over time. For example, while a set of products may yield a high utility (profit) over a year, that utility may fluctuate from weeks to weeks. To discover patterns that have a stable utility and hence that are more suitable for decision-making, this paper redefines HUIM as the task of discovering Stable High Utility Itemsets (StableHUI). An efficient tree-based and pattern-growth algorithm named Stable-Growth is proposed to extract all the StableHUI. Several experiments on two real-world datasets and two synthetic datasets show that Stable-Growth is up to 60% faster than a baseline and that it can filter out numerous unstable HUI.
AB - High Utility Itemset Mining (HUIM) aims at finding all sets of items that have high importance in a database, as measured by a utility function. Although HUIM has many applications, a key limitation is that the discovered patterns often have an unstable utility over time. For example, while a set of products may yield a high utility (profit) over a year, that utility may fluctuate from weeks to weeks. To discover patterns that have a stable utility and hence that are more suitable for decision-making, this paper redefines HUIM as the task of discovering Stable High Utility Itemsets (StableHUI). An efficient tree-based and pattern-growth algorithm named Stable-Growth is proposed to extract all the StableHUI. Several experiments on two real-world datasets and two synthetic datasets show that Stable-Growth is up to 60% faster than a baseline and that it can filter out numerous unstable HUI.
KW - Stability
KW - data mining
KW - high utility itemset
KW - pattern mining
UR - http://www.scopus.com/inward/record.url?scp=85122637002&partnerID=8YFLogxK
U2 - 10.1145/3487664.3487704
DO - 10.1145/3487664.3487704
M3 - Conference contribution
AN - SCOPUS:85122637002
T3 - ACM International Conference Proceeding Series
SP - 296
EP - 302
BT - 23rd International Conference on Information Integration and Web Intelligence, iiWAS 2021 - Proceedings
A2 - Pardede, Eric
A2 - Santiago, Maria-Indrawan
A2 - Haghighi, Pari Delir
A2 - Steinbauer, Matthias
A2 - Khalil, Ismail
A2 - Kotsis, Gabriele
PB - Association for Computing Machinery
T2 - 23rd International Conference on Information Integration and Web Intelligence, iiWAS 2021
Y2 - 29 November 2021 through 1 December 2021
ER -