Results 31 to 40 of about 498 (210)

CLS-Miner: efficient and effective closed high-utility itemset mining [PDF]

, 2018
High-utility itemset mining (HUIM) is a popular data mining task with applications in numerous domains. However, traditional HUIM algorithms often produce a very large set of high-utility itemsets (HUIs).
Quang-Huy Duong, Philippe Fournier-Viger, Thu-Lan Dam, Dam, Thu-Lan, Kenli Li, Li, Kenli, Duong, Quang-Huy, Fournier-Viger, Philippe   +7 more
core   +2 more sources

Mining Association rules for Low-Frequency itemsets. [PDF]

PLoS ONE, 2018
High utility itemset mining has become an important and critical operation in the Data Mining field. High utility itemset mining generates more profitable itemsets and the association among these itemsets, to make business decisions and strategies ...
Jimmy Ming-Tai Wu, Justin Zhan, Sanket Chobe   +2 more
doaj   +1 more source

Generic Itemset Mining Based on Reinforcement Learning

IEEE Access, 2022
One of the biggest problems in itemset mining is the requirement of developing a data structure or algorithm, every time a user wants to extract a different type of itemsets.
Kazuma Fujioka, Kimiaki Shirahama
doaj   +1 more source

A Robust Technique for Closed Frequent and High Utility Itemsets Mining: Closed-FHUIM

IEEE Access
Frequent itemset mining (FIM) and high utility itemset mining (HUIM) are popular data mining techniques used in various real-world applications such as retail-market, bio-medicine, and click-stream analysis.
Muhammad Waheed Ashraf, M. Asif Naeem, Heejeong Jasmine Lee   +2 more
doaj   +1 more source

Actionable high-coherent-utility fuzzy itemset mining

, 2016
Many fuzzy data mining approaches have been proposed for finding fuzzy association rules with the predefined minimum support from quantitative transaction databases.
Chen, C. H.;Li, A. F.;Lee, Y. C., Chen, Chun-hao   +1 more
core   +1 more source

Parallel Mining Algorithm for the Enumeration Space of Closed High Utility Itemsets

Journal of Harbin University of Science and Technology
To address the issues of result redundancy and time overhead in high-dimensional data environments, a closed high utility itemset mining algorithm, SpCHUIM (Closed High Utility Itemsets Mining on Spark), is proposed.
LI Chengyan, SUN Anqi, LIU Songlin
doaj   +1 more source

A survey of itemset mining

, 2017
Itemset mining is an important subfield of data mining, which consists of discovering interesting and useful patterns in transaction databases. The traditional task of frequent itemset mining is to discover groups of items (itemsets) that appear ...
Jerry Chun‐Wei Lin, Vo, Bay, Bay Vo, Tin Truong Chi, Zhang, Ji, Philippe Fournier‐Viger, Hoai Bac Le, Chi, Tin Truong, Le, Hoai Bac, Lin, Jerry Chun-Wei, Ji Zhang, Fournier-Viger, Philippe   +11 more
core   +1 more source

Mining of high average-utility patterns with item-level thresholds

, 2019
In this paper, we introduce a level-wise algorithm named High Average-Utility Itemset Mining with Multiple Minimum Average-Utility threshold (HAUIM-MMAU), which relies on a novel transaction-maximum utility downward closure (TMUDC) property and a concept
Zhang, Ji, Guo, Xiangmin, Li, Ting, Lin, Jerry Chun-Wei, Fournier-Viger, Philippe   +4 more
core   +1 more source

An Evolutionary Algorithm to Mine High-Utility Itemsets

Advances in Electrical and Electronic Engineering, 2015
High-utility itemset mining (HUIM) is a critical issue in recent years since it can be used to reveal the profitable products by considering both the quantity and profit factors instead of frequent itemset mining (FIM) of association rules (ARs). In this
Jerry Chun-Wei Lin, Lu Yang, Philippe Fournier-Viger, Jaroslav Frnda, Lukas Sevcik, Miroslav Voznak   +5 more
doaj   +1 more source

Personalized and Explainable Aspect‐Based Recommendation Using Latent Opinion Groups

Computational Intelligence, Volume 42, Issue 2, April 2026.
ABSTRACT The problem of explainable recommendation—supporting the recommendation of a product or service with an explanation of why the item is a good choice for the user—is attracting substantial research attention recently. Recommendations associated with an explanation of how the aspects of the chosen item may meet the needs and preferences of the ...
Maryam Mirzaei, Jörg Sander, Eleni Stroulia   +2 more
wiley   +1 more source