Results 41 to 50 of about 498 (210)
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 +3 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 +3 more
doaj +1 more source
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 +3 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
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 +2 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
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 +5 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
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
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 +8 more
doaj +1 more source