Results 11 to 20 of about 905 (211)

Incremental high average-utility itemset mining: survey and challenges [PDF]

open access: yesScientific Reports
The High Average Utility Itemset Mining (HAUIM) technique, a variation of High Utility Itemset Mining (HUIM), uses the average utility of the itemsets. Historically, most HAUIM algorithms were designed for static databases.
Jing Chen   +6 more
doaj   +3 more sources

Approximate Parallel High Utility Itemset Mining [PDF]

open access: yesBig Data Research, 2016
High utility itemset mining discovers itemsets whose utility is above a given threshold, where the utility measures the importance of an itemset. It overcomes the limitation of frequent pattern mining, which uses frequency as its quality measure. To speed up the performance for mining high utility itemsets, many algorithms have been proposed which ...
Yan Chen 0021, Aijun An
openaire   +2 more sources

IPHM: Incremental periodic high-utility mining algorithm in dynamic and evolving data environments [PDF]

open access: yesHeliyon
Periodic high-utility itemset (PHUI) mining can extend beyond the conventional approach of high-utility itemset mining by uncovering recurring customer purchase behaviors common in real-life scenarios (e.g., buying apples and oranges every three days or ...
Huiwu Huang, Shixi Chen, Jiahui Chen
doaj   +2 more sources

A Parallel High-Utility Itemset Mining Algorithm Based on Hadoop [PDF]

open access: yesComplex System Modeling and Simulation, 2023
High-utility itemset mining (HUIM) can consider not only the profit factor but also the profitable factor, which is an essential task in data mining. However, most HUIM algorithms are mainly developed on a single machine, which is inefficient for big ...
Zaihe Cheng   +3 more
doaj   +2 more sources

HUIL-TN & HUI-TN: Mining high utility itemsets based on pattern-growth. [PDF]

open access: yesPLoS ONE, 2021
In recent years, high utility itemsets (HUIs) mining has been an active research topic in data mining. In this study, we propose two efficient pattern-growth based HUI mining algorithms, called High Utility Itemset based on Length and Tail-Node tree ...
Le Wang, Shui Wang
doaj   +2 more sources

Behavior Decoding Delineates Seizure Microfeatures and Associated Sudden Death Risks in Mouse Models of Epilepsy [PDF]

open access: yesAnnals of Neurology, Volume 99, Issue 1, Page 231-247, January 2026.
Objective Behavior and motor manifestations are distinctive yet often overlooked features of epileptic seizures. Seizures can result in transient disruptions in motor control, often organized into specific behavioral sequences that can inform seizure types, onset zones, and outcomes.
Yuyan Shen   +8 more
wiley   +2 more sources

Proof Learning in PVS With Utility Pattern Mining [PDF]

open access: yesIEEE Access, 2020
Interactive theorem provers (ITPs) are software tools that allow human users to write and verify formal proofs. In recent years, an emerging research area in ITPs is proof mining, which consists of identifying interesting proof patterns that can be used ...
M. Saqib Nawaz   +2 more
doaj   +2 more sources

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

open access: yesPLoS 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   +2 more
doaj   +2 more sources

A high utility itemsets mining algorithm based on co-evolution [PDF]

open access: yesScientific Reports
Metaheuristic high utility itemsets mining algorithms often face challenges such as poor initial population quality, low time efficiency, and itemsets loss due to premature convergence. To address these issues, this study proposes a high utility itemsets
Wenyan Yang   +4 more
doaj   +2 more sources

Mining Locally Trending High Utility Itemsets [PDF]

open access: yesAdvances in Knowledge Discovery and Data Mining24th Pacific-Asia Conference, 2020
High utility itemset mining consists of identifying all the sets of items that appear together and yield a high profit in a customer transaction database. Recently, this problem was extended to discover trending high utility itemsets (itemsets that yield an increasing or decreasing profit over time).
Philippe Fournier-Viger   +3 more
openaire   +2 more sources

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