Results 41 to 50 of about 5,295 (219)

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

Incrementally Updating the Discovered High Average-Utility Patterns With the Pre-Large Concept

IEEE Access, 2020
High average-utility itemset mining (HAUIM) is an extension of high-utility itemset mining (HUIM), which provides a reliable measure to reveal utility patterns by considering the length of the mined pattern.
Jimmy Ming-Tai Wu, Qian Teng, Jerry Chun-Wei Lin, Chien-Fu Cheng   +3 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

Cross-Entropy Assisted Optimization Technique for High Utility Itemset Mining from the Transactional Database

Communications on Applied Nonlinear Analysis
High Utility Itemset Mining (HUIM) is the process of discovering profitable itemsets in a transactional database with a high utility or profit range. This technique is mainly used to unearth the prominent patterns and insights from large volumes of data.
V. Jeevika Tharini
semanticscholar   +1 more source

Global Copper Deposit Dataset: A New Open‐Source Database for Advanced Data Analysis and Exploration Targeting

Geoscience Data Journal, Volume 13, Issue 1, January 2026.
We build a new, open‐source global copper deposit dataset (GCDD), facilitating AI‐driven data analysis for exploration targeting and improving our understanding of copper mineralizing systems and their mappable expressions. The GCDD hosts information about 1483 copper deposits worldwide, capturing key deposit attributes such as location, genetic type ...
Bin Wang, Renguang Zuo, Oliver P. Kreuzer   +2 more
wiley   +1 more source

EHAUPM: Efficient High Average-Utility Pattern Mining With Tighter Upper Bounds

IEEE Access, 2017
High-utility itemset mining (HUIM) has become a popular data mining task, as it can reveal patterns that have a high-utility, contrarily to frequent pattern mining, which focuses on discovering frequent patterns.
Jerry Chun-Wei Lin, Shifeng Ren, Philippe Fournier-Viger, Tzung-Pei Hong   +3 more
doaj   +1 more source

A Design‐Driven Machine Learning Approach for Invariant Mining in a Smart Grid

IET Cyber-Physical Systems: Theory &Applications, Volume 11, Issue 1, January/December 2026.
An ICS is vulnerable to cyber‐attacks arising from within its communication network or directly from the SCADA and devices such as PLCs. The study reported here presents a scenario‐specific invariant mining approach to detect anomalies in plant behaviour.
Danish Hudani, Muhammad Haseeb, Muhammad Taufiq, Muhammad Azmi Umer, Nandha Kumar Kandasamy, Aditya P. Mathur   +5 more
wiley   +1 more source

Efficient Utility Tree-Based Algorithm to Mine High Utility Patterns Having Strong Correlation

Complexity, 2021
High Utility Itemset Mining (HUIM) is one of the most investigated tasks of data mining. It has broad applications in domains such as product recommendation, market basket analysis, e-learning, text mining, bioinformatics, and web click stream analysis ...
Rashad Saeed, Azhar Rauf, Fahmi H. Quradaa, Syed Muhammad Asim   +3 more
doaj   +1 more source

From Prediction to Prevention: Using Text Mining and Explainable Machine Learning for Urban Bus Accident Analytics

Risk Analysis, Volume 46, Issue 1, January 2026.
ABSTRACT Urban bus accidents present major safety and operational challenges, particularly in densely populated metropolitan areas. This study develops a machine learning‐based analytical framework to identify, quantify, and interpret the factors associated with severe bus accidents.
Bowei Chen, Yufei Huang, Yu Zheng, Xiaofeng Liu   +3 more
wiley   +1 more source

EXPLOIT MINING HIGH UTILITY ITEMSETS WITH NEGATIVE UNIT PROFITS FROM VERTICALLY DISTRIBUTED DATABASES

Tạp chí Khoa học Đại học Đà Lạt, 2020
High Utility Itemset (HUI) mining is an important problem in the data mining literature that considers the utilities for businesses of items (such as profits and margins) that are discovered from transactional databases.
Cao Tùng Anh, Ngô Quốc Huy, Võ Hoàng Khang   +2 more
doaj   +1 more source