Results 21 to 30 of about 311 (178)

A One-Phase Tree-Structure Method to Mine High Temporal Fuzzy Utility Itemsets

Applied Sciences, 2022
Compared to fuzzy utility itemset mining (FUIM), temporal fuzzy utility itemset mining (TFUIM) has been proposed and paid attention to in recent years.
Tzung-Pei Hong, Cheng-Yu Lin, Wei-Ming Huang, Shu-Min Li, Shyue-Liang Wang, Jerry Chun-Wei Lin   +5 more
doaj   +1 more source

TUB-HAUPM: Tighter Upper Bound for Mining High Average-Utility Patterns

IEEE Access, 2018
High-utility itemset mining (HUIM) has been gaining popularity in the field of data mining. Frequent itemset mining used to be the main tool to reveal high-frequency patterns but failed to consider the concept of profit.
Jimmy Ming-Tai Wu, Jerry Chun-Wei Lin, Matin Pirouz, Philippe Fournier-Viger   +3 more
doaj   +1 more source

An Efficient Approach for Mining Reliable High Utility Patterns

IEEE Access, 2022
Utility mining is one of the most thriving research topics with a wide range of real-world applications. High utility pattern mining uses a utility function to extract all desired patterns that exceed a minimum utility threshold.
Mohammed A. Fouad, Wedad Hussein, Sherine Rady, Philip S. Yu, Tarek F. Gharib   +4 more
doaj   +1 more source

LUIM: New Low-Utility Itemset Mining Framework

IEEE Access, 2019
High-utility itemset mining (HUIM), which is the detection of high-utility itemsets (HUIs) in a transactional database, provides the decision maker with greater flexibility to exploit item utilities, such as quantity and profits, to extract remarkable ...
Naji Alhusaini, Saleem Karmoshi, Ammar Hawbani, Li Jing, Abdullah Alhusaini, Yaser Al-sharabi   +5 more
doaj   +1 more source

Mining Correlated High Utility Itemsets in One Phase

IEEE Access, 2020
High-utility itemset mining (HUIM) in transaction databases has been extensively studied to discover interesting itemsets from users' purchase behaviors. With this, business managers can adjust their sale strategies appropriately to increase profit. HUIM
Bay Vo, Le V. Nguyen, Vinh V. Vu, Mi T. H. Lam, Thuy T. M. Duong, Ly T. Manh, Thuy T. T. Nguyen, Loan T. T. Nguyen, Tzung-Pei Hong   +8 more
doaj   +1 more source

MINING OF HIGH-UTILITY ITEMSETS WITH NEGATIVE UTILITY

JOURNAL OF TECHNOLOGY & INNOVATION, 2020
The goal of the high-utility itemset mining task is to discover combinations of items that yield high profits from transactional databases. HUIM is a useful tool for retail stores to analyze customer behaviors. However, in the real world, items are found with both positive and negative utility values.
Tung N.T, Nguyen Le Van, Trinh Cong Nhut, Tran Van Sang   +3 more
openaire   +1 more source

A Parallel High-Utility Itemset Mining Algorithm Based on Hadoop

Complex 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, Wei Shen, Wei Fang, Jerry Chun-Wei Lin   +3 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

Approximate Parallel High Utility Itemset Mining [PDF]

Big 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, Aijun An
openaire   +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