Results 41 to 50 of about 2,597 (181)
Personalized and Explainable Aspect‐Based Recommendation Using Latent Opinion Groups
Computational Intelligence, Volume 42, Issue 2, April 2026.ABSTRACT The problem of explainable recommendation—supporting the recommendation of a product or service with an explanation of why the item is a good choice for the user—is attracting substantial research attention recently. Recommendations associated with an explanation of how the aspects of the chosen item may meet the needs and preferences of the ...
Maryam Mirzaei +2 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
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
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
Annals of Neurology, Volume 99, Issue 1, Page 231-247, January 2026.Objective Behavior and motor manifestations are distinctive yet often overlooked features of epileptic seizures. Seizures can result in transient disruptions in motor control, often organized into specific behavioral sequences that can inform seizure types, onset zones, and outcomes.
Yuyan Shen +8 more
wiley +1 more source
Proposed Algorithm for Extracting Association Rule Depend on Closed Frequent Itemset (EACFI) [PDF]
Engineering and Technology Journal, 2011 Association rules are important one of data mining activities. All algorithms of association rule mining consist of finding frequency of itemsets, which satisfy a minimum support threshold, and then compute confidence percentage for each k-itemsets to ...
Emad k. Jbbar, Yaser Munther
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
Mining all non-derivable frequent itemsets
, 2002 Recent studies on frequent itemset mining algorithms resulted in significant performance improvements. However, if the minimal support threshold is set too low, or the data is highly correlated, the number of frequent itemsets itself can be prohibitively
Toivonen, H. +4 more
core +1 more source
Efficient Associate Rules Mining Based on Topology for Items of Transactional Data
Mathematics, 2023 A challenge in association rules’ mining is effectively reducing the time and space complexity in association rules mining with predefined minimum support and confidence thresholds from huge transaction databases.
Bo Li, Zheng Pei, Chao Zhang, Fei Hao
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