Results 41 to 50 of about 9,424 (197)
Mining frequent itemsets over uncertain databases [PDF]
Proceedings of the VLDB Endowment, 2012 In recent years, due to the wide applications of uncertain data, mining frequent itemsets over uncertain databases has attracted much attention. In uncertain databases, the support of an itemset is a random variable instead of a fixed occurrence counting of this itemset.
Tong, Yongxin +3 more
openaire +3 more sources
Reading Research Quarterly, Volume 61, Issue 2, April/May/June 2026.This study introduces and validates the Self‐Efficacy for Online Reading Questionnaire (SEORQ), a process‐grounded instrument designed to measure secondary students' efficacy in executing the core demands of online reading. The model conceptualizes online reading self‐efficacy as a multidimensional construct encompassing five interrelated processes ...
SeongYeup Kim +2 more
wiley +1 more source
A novel association rule mining approach using TID intermediate itemset. [PDF]
PLoS ONE, 2018 Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern.
Iyad Aqra +7 more
doaj +1 more source
Sistem Rekomendasi Buku Perpustakaan Menggunakan Algoritma Frequent Pattern Growth
Techno.Com, 2022 Perpustakaan memiliki pelayanan utama memfasilitasi peminjaman buku, untuk memudahkan anggota perpustakaan menemukan buku yang tepat, perpustakaan dapat dilengkapi dengan sistem pencarian buku.
Endang Retnoningsih +1 more
doaj +1 more source
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
An Improved Apriori Algorithm for Association Rules
, 2014 There are several mining algorithms of association rules. One of the most popular algorithms is Apriori that is used to extract frequent itemsets from large database and getting the association rule for discovering the knowledge. Based on this algorithm,
Al-Maolegi, Mohammed, Arkok, Bassam
core +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
Mining Top-K Frequent Itemsets Through Progressive Sampling
, 2010 We study the use of sampling for efficiently mining the top-K frequent itemsets of cardinality at most w. To this purpose, we define an approximation to the top-K frequent itemsets to be a family of itemsets which includes (resp., excludes) all very ...
Andrea Pietracaprina +8 more
core +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
A Robust Technique for Closed Frequent and High Utility Itemsets Mining: Closed-FHUIM
IEEE AccessFrequent itemset mining (FIM) and high utility itemset mining (HUIM) are popular data mining techniques used in various real-world applications such as retail-market, bio-medicine, and click-stream analysis.
Muhammad Waheed Ashraf +2 more
doaj +1 more source