Results 61 to 70 of about 2,346 (201)
FTKHUIM: A Fast and Efficient Method for Mining Top-K High-Utility Itemsets
IEEE Access, 2023 High-utility itemset mining (HUIM) is an important task in the field of knowledge data discovery. The large search space and huge number of HUIs are the consequences of applying HUIM algorithms with an inappropriate user-defined minimum utility threshold
Vinh V. Vu +8 more
doaj +1 more source
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 +6 more
wiley +1 more source
Utility-driven Data Analytics on Uncertain Data
, 2019 Modern Internet of Things (IoT) applications generate massive amounts of data, much of it in the form of objects/items of readings, events, and log entries.
Chao, Han-Chieh +4 more
core +1 more source
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 +3 more
wiley +1 more source
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 +2 more
doaj +1 more source
Statistical strategies for pruning all the uninteresting association rules [PDF]
, 2003 We propose a general framework to describe formally the problem of capturing the intensity of implication for association rules through statistical metrics.
Casas Garriga, Gemma
core +1 more source
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 +4 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 +3 more
doaj +1 more source
Computational Intelligence, Volume 41, Issue 4, August 2025.ABSTRACT Machine learning techniques are increasingly used for high‐stakes decision‐making, such as college admissions, loan attribution, or recidivism prediction. Thus, it is crucial to ensure that the models learnt can be audited or understood by human users, do not create or reproduce discrimination or bias and do not leak sensitive information ...
Julien Ferry +4 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 +3 more
doaj +1 more source