Results 51 to 60 of about 530 (210)

Critical Review for One‐Class Classification: Recent Advances and Reality Behind Them

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 1, March 2026.
This review presents a new taxonomy to summarize one‐class classification (OCC) algorithms and their applications. The main argument is that OCC should not learn multiple classes. The paper highlights common violations of OCC involving multiple classes.
Toshitaka Hayashi, Dalibor Cimr, Hamido Fujita, Richard Cimler   +3 more
wiley   +1 more source

Mining of high average-utility patterns with item-level thresholds

, 2019
In this paper, we introduce a level-wise algorithm named High Average-Utility Itemset Mining with Multiple Minimum Average-Utility threshold (HAUIM-MMAU), which relies on a novel transaction-maximum utility downward closure (TMUDC) property and a concept
Zhang, Ji, Guo, Xiangmin, Li, Ting, Lin, Jerry Chun-Wei, Fournier-Viger, Philippe   +4 more
core   +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

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

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

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

High utility-itemset mining and privacy-preserving utility mining

, 2016
SummaryIn recent decades, high-utility itemset mining (HUIM) has emerging a critical research topic since the quantity and profit factors are both concerned to mine the high-utility itemsets (HUIs).
Liu, Qiankun, Frnda, Jaroslav, Yang, Lu, Sevcik, Lukas, Voznak, Miroslav, Lin, Jerry Chun-Wei, Fournier-Viger, Philippe, Gan, Wensheng   +7 more
core   +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

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

Incrementally updating the high average-utility patterns with pre-large concept [PDF]

, 2020
High-utility itemset mining (HUIM) is considered as an emerging approach to detect the high-utility patterns from databases. Most existing algorithms of HUIM only consider the itemset utility regardless of the length.
Djenouri, Youcef, Cheng, Chien-Fu, Pirouz, Matin, Ahmed, Usman, Lin, Jerry Chun-Wei   +4 more
core   +1 more source