Results 41 to 50 of about 846,106 (226)

A Deduplication and Extraction Algorithm for Frequent Itemsets of Overlapping Data Between Power Categories Based on Variable Time Windows

International Journal of Computational Intelligence Systems
In the process of data extraction, the rigid partitioning mechanism of fixed time windows leads to spatiotemporal heterogeneity mismatches in data distribution, resulting in semantic confusion and redundancy accumulation in mining results. To address the
Jie Zhang, Jing Liu, Chenyang Hu, Xin Huang   +3 more
doaj   +1 more source

Incremental Closed Frequent Itemsets Mining-Based Approach Using Maximal Candidates

IEEE Access
Incremental frequent itemset mining aims to efficiently update frequent itemsets without recalculating them from scratch, making it suitable for streaming data and real-time analytics.
Mohammed A. Al-Zeiadi, Basheer M. Al-Maqaleh   +1 more
doaj   +1 more source

Consumer Behavior Analysis in Digital Marketing Using AI and Big Data Analytics: A Narrative Review and Methodological Taxonomy

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 3, September 2026.
AI and Big Data in Consumer Behavior Analysis. ABSTRACT The rapid expansion of digital consumer data has challenged traditional approaches to understanding behavior in digital marketing. Existing reviews often focus on individual methods and give limited guidance on how analytical techniques compare or how they should be selected for specific marketing
Leonidas Theodorakopoulos, Alexandra Theodoropoulou   +1 more
wiley   +1 more source

A GENERAL SURVEY ON FREQUENT PATTERN MINING USING GENETIC ALGORITHM [PDF]

ICTACT Journal on Soft Computing, 2012
In recent years, data mining is an important aspect for generating association rules among the large number of itemsets. Association rule mining is one of the techniques in data mining that that has two sub processes. First, the process called as finding
K. Poornamala, R. Lawrance
doaj  

An Association Rule Mining Algorithm Based on a Boolean Matrix

Data Science Journal, 2007
Association rule mining is a very important research topic in the field of data mining. Discovering frequent itemsets is the key process in association rule mining.
Hanbing Liu, Baisheng Wang
doaj   +1 more source

Polypharmacy burden and incident epilepsy among older adults in the United States

Epilepsia Open, Volume 11, Issue 4, Page 1370-1381, August 2026.
Abstract Objectives To estimate the prevalence of polypharmacy among older adults with incident epilepsy and to describe the most common combinations of drug classes filled prior to epilepsy diagnosis. Polypharmacy—the concurrent use of multiple medications—is common in older adults with epilepsy, but little is known about its burden and specific ...
Galen Shearn‐Nance, Long Vu, Hannah L. Fein, Wyatt P. Bensken, Jorden G. Rieke, Martha Sajatovic, Gena Ghearing, David F. Warner, Siran M. Koroukian, Nicholas K. Schiltz   +9 more
wiley   +1 more source

Memory-efficient frequent-itemset mining

Proceedings of the 14th International Conference on Extending Database Technology, 2011
Efficient discovery of frequent itemsets in large datasets is a key component of many data mining tasks. In-core algorithms---which operate entirely in main memory and avoid expensive disk accesses---and in particular the prefix tree-based algorithm FP-growth are generally among the most efficient of the available algorithms.
Benjamin Schlegel, Rainer Gemulla, Wolfgang Lehner   +2 more
openaire   +3 more sources

A weighted frequent itemset mining algorithm for intelligent decision in smart systems

IEEE Access, 2018
Intelligent decision is the key technology of smart systems. Data mining technology has been playing an increasingly important role in decision-making activities.
Xuejian Zhao, Xinhui Zhang, Pan Wang, Songle Chen, Zhixin Sun   +4 more
doaj   +1 more source

Globally Valid Rule‐Based Explanations for Black‐Box Models

Computational Intelligence, Volume 42, Issue 4, August 2026.
ABSTRACT Black‐box explanation methods such as Lime define a neighborhood around the query example, learn an interpretable local surrogate model in this neighborhood, and use this local surrogate model for its explanation. Lore and Anchors are two such methods, which deliver local explanations in the form of IF‐THEN rules.
Van Quoc Phuong Huynh, Florian Beck, Josef Küng, Johannes Fürnkranz   +3 more
wiley   +1 more source

Double‐Edged Sword of Social Media Algorithms: Assessing the Risks to University Cybersecurity and Student Data Privacy

Engineering Reports, Volume 8, Issue 5, May 2026.
Social media algorithms drive a hidden risk chain: over‐disclosure → behavioral fusion → targeted attacks. We propose a 128‐dim, law‐aware risk scoring model with Drools‐based dynamic alerts for universities. ABSTRACT As universities undergo accelerated digital transformation, social media algorithms—while streamlining campus services—have emerged as a
Weishu Ye, Zhi Li
wiley   +1 more source