Results 61 to 70 of about 659,904 (212)

Mining High-Efficiency Itemsets with Negative Utilities

Mathematics
High-efficiency itemset mining has recently emerged as a new problem in itemset mining. An itemset is classified as a high-efficiency itemset if its utility-to-investment ratio meets or exceeds a specified efficiency threshold.
Irfan Yildirim
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

An Efficient Approach for Mining High Average-Utility Itemsets in Incremental Database

Engineering Proceedings
Traditional high-utility itemset (HUI) mining methods tend to overestimate utility for long itemsets, leading to biased results. High average-utility itemset (HAUI) mining addresses this problem by normalizing utility with itemset length.
Ye-In Chang, Chen-Chang Wu, Hsiang-En Kuo   +2 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

Integrated Approach for Privacy Preserving Itemset Mining

, 2011
In this work, we propose an integrated itemset hiding algorithm that eliminates the need of pre-mining and post-mining and uses a simple heuristic in selecting the itemset and the item in itemset for distortion.
Belgin Ergenç, Ergenç, Belgin, Barış Yıldız, Yildiz, Bariş   +3 more
core   +1 more source

Efficient Mining of Frequent Itemsets Using Only One Dynamic Prefix Tree

IEEE Access, 2020
Frequent itemset mining is a fundamental problem in data mining area because frequent itemsets have been extensively used in reasoning, classifying, clustering, and so on.
Jun-Feng Qu, Bo Hang, Zhao Wu, Zhongbo Wu, Qiong Gu, Bo Tang   +5 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

Scaling up Pattern Induction for Web Relation Extraction through Frequent Itemset Mining [PDF]

, 2008
Blohm S, Cimiano P. Scaling up Pattern Induction for Web Relation Extraction through Frequent Itemset Mining. In: Adrian B, Neumann G, Troussov A, Popov B, eds.
Troussov, Alexander, Adrian, Benjamin, Neumann, Günter, Popov, Borislav, Blohm, Sebastian, Cimiano, Philipp ; https://orcid.org/   +5 more
core  

Frequent Itemset Mining for Big Data [PDF]

, 2017
Traditional data mining tools, developed to extract actionable knowledge from data, demonstrated to be inadequate to process the huge amount of data produced nowadays.
Pulvirenti, Fabio
core   +1 more source

EFFICIENT FREQUENT ITEMSET DISCOVERY THROUGH HIERARCHICAL HUFFMAN ENCODING [PDF]

ICTACT Journal on Soft Computing
Frequent itemsets mining holds a crucial position in the field of data mining; however, traditional algorithms like Apriori and FP-Growth often encounter efficiency and memory consumption issues when handling large-scale datasets, which not only makes ...
Dai Xin, Hao Xue
doaj   +1 more source