Results 31 to 40 of about 15,856,028 (211)

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

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

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 Efficient Approach for Mining High Average-Utility Itemsets in Incremental Database

Engineering Proceedings
Traditional high-utility itemset (HUI) mining methods tend to overestimate utility for long itemsets, leading to biased results. High average-utility itemset (HAUI) mining addresses this problem by normalizing utility with itemset length.
Ye-In Chang, Chen-Chang Wu, Hsiang-En Kuo   +2 more
doaj   +1 more source

Improved Genetic Algorithm for High-Utility Itemset Mining

IEEE Access, 2019
High-utility itemset mining (HUIM) is an important research topic in the data mining field. Typically, traditional HUIM algorithms must handle the exponential problem of huge search space when the database size or number of distinct items is very large ...
Qiang Zhang, Wei Fang, Jun Sun, Quan Wang   +3 more
doaj   +1 more source

Association Rule Mining for Accidental Dwelling Fire Incidence Data Analysis in Greater Manchester, UK

Fire and Materials, EarlyView.
ABSTRACT Association rule mining was used to identify patterns in accidental dwelling fire incidents attended by Greater Manchester Fire and Rescue Service over the period 2013/14 to 2023/24. The association rule mining process identified relationships between cooking fire incidence, distraction, living alone, deprivation, and fire injury.
M. Taylor, R. Lyon, D. Doolan, E. Dean, J. Fielding, M. Thomas   +5 more
wiley   +1 more source

On efficiently mining high utility sequential patterns

, 2016
High utility sequential pattern mining is an emerging topic in pattern mining, which refers to identify sequences with high utilities (e.g., profits) but probably with low frequencies. To identify high utility sequential patterns, due to lack of downward
Wang, Jun-Zhe;Huang, Jiun-Long;Chen, Yi-Cheng
core   +1 more source