Results 61 to 70 of about 15,856,028 (211)

PUC: parallel mining of high-utility itemsets with load balancing on spark

Journal of Intelligent Systems, 2022
Distributed programming paradigms such as MapReduce and Spark have alleviated sequential bottleneck while mining of massive transaction databases. Of significant importance is mining High Utility Itemset (HUI) that incorporates the revenue of the items ...
Brahmavar Anup Bhat, Sheeranalli Venkatarama Harish, Maiya Geetha   +2 more
doaj   +1 more source

Extraction of Safe Operation Rules and Identification of Vulnerable Nodes in Power Grids Based on Time‐Series Association Analysis

IET Generation, Transmission &Distribution, Volume 20, Issue 1, January/December 2026.
This paper presents a data‐driven framework for operational safety rule extraction and vulnerable node identification in power grids with high renewable penetration. The effectiveness of the proposed method is verified on the IEEE 39‐bus system for static security assessment. ABSTRACT High renewable energy penetration introduces significant uncertainty
Zhilin Huang, Zheng Xu, Yudun Li, Yanqi Hou, Facai Xing, Zhi Gao, Yiping Yu   +6 more
wiley   +1 more source

High Utility Itemset Mining by Using Binary PSO Algorithm

, 2022
The goal of pattern mining is to find some novel patterns from a given database. High utility itemset mining (HUIM) is a research direction of the pattern mining as a sub-domain of data mining.
TAO BODONG
core  

Frequent Closed High-Utility Itemset Mining Algorithm Based on Leiden Community Detection and Compact Genetic Algorithm

IEEE Access
Traditional pattern mining algorithms are based on tree and linked list structures. However, they often only consider a single factor of frequency or utility and have to deal with exponential search spaces as well as generate numerous candidates.
Xiumei Zhao, Xincheng Zhong, Bing Han
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

Correlation Analysis of Influencing Factors of Autonomous Vehicle Accidents Based on Improved Apriori Algorithm

Journal of Advanced Transportation, Volume 2026, Issue 1, 2026.
The purpose of this study was to explore the risk factors for autonomous vehicle (AV) crashes and their interdependencies. A total of 659 AV crash data were collected between 2018 and July 2024 from AV crash reports published by the California Department of Motor Vehicles.
Tao Wang, Wenzhi Tang, Juncong Chen, Wenwu Chen, Mohammad Rezwan Habib   +4 more
wiley   +1 more source

mHUIMiner: A Fast High Utility Itemset Mining Algorithm for Sparse Datasets

, 2017
High utility itemset mining is the problem of finding sets of items whose utilities are higher than or equal to a specific threshold. We propose a novel technique called mHUIMiner, which utilises a tree structure to guide the itemset expansion process to
Peng, AY, Alex Yuxuan Peng, Riddle, Patricia, Yun Sing Koh, Koh, Yun Sing, Patricia Riddle   +5 more
core   +1 more source

RPriori: A Divide‐and‐Conquer Frequent Itemset Mining Algorithm With Improved Time‐Space Efficiency on Large Transactional Data

Complexity, Volume 2026, Issue 1, 2026.
Frequent itemset mining (FIM) is a fundamental task in data mining with applications ranging from market basket analysis and recommendation systems to fraud detection and bioinformatics. However, mining frequent itemsets from massive datasets remains computationally challenging due to high execution time and memory consumption.
Rahat Ali Shah, Jamal Uddin, Hameed Hussain, Khaistah Khan, Shujaat Ali, Dilawar Shah, Muhammad Tahir, Shonak Bansal   +7 more
wiley   +1 more source

Metaheuristics for Frequent and High-Utility Itemset Mining

, 2019
Metaheuristics are often used to solve combinatorial problems. They can be viewed as general purpose problem-solving approaches based on stochastic methods, which explore very large search spaces to find near-optimal solutions in a reasonable time.
Djenouri, Youcef, Philippe Fournier-Viger, Youcef Djenouri, Lin, Jerry Chun Wei, Belhadi, Asma, Asma Belhadi, Jerry Chun-Wei Lin, Fournier-Viger, Philippe   +7 more
core   +1 more source

A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit Databases

IEEE Access, 2020
Analyzing customer transactions to discover high-utility itemsets is a popular task, which consists of finding the sets of items that are purchased together and yield a high profit.
Bay Vo, Loan T.T. Nguyen, Trinh D.D. Nguyen, Philippe Fournier-Viger, Unil Yun   +4 more
doaj   +1 more source