Results 41 to 50 of about 8,898 (200)
The MapReduce Model on Cascading Platform for Frequent Itemset Mining
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2018 The implementation of parallel algorithms is very interesting research recently. Parallelism is very suitable to handle large-scale data processing. MapReduce is one of the parallel and distributed programming models.
Nur Rokhman, Amelia Nursanti
doaj +1 more source
SECURE ASSOCIATION RULE MINING ON VERTICALLY PARTITIONED DATA USING FULLY HOMOMORPHIC ENCRYPTION
ICTACT Journal on Soft Computing, 2021 Cloud Computing is a leading innovation technology that guides to access applications over the web. The data owner’s data can be gotten to and controlled in the cloud.
M Yogasini, B N Prathibha
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A Model-Based Frequency Constraint for Mining Associations from Transaction Data
, 2006 Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an association, is used as the primary indicator of the associations's significance.
Hahsler, Michael
core +3 more sources
Right-Hand Side Expanding Algorithm for Maximal Frequent Itemset Mining
Applied Sciences, 2021 When it comes to association rule mining, all frequent itemsets are first found, and then the confidence level of association rules is calculated through the support degree of frequent itemsets.
Yalong Zhang +4 more
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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
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 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
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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
Privacy Preserving Utility Mining: A Survey
, 2018 In big data era, the collected data usually contains rich information and hidden knowledge. Utility-oriented pattern mining and analytics have shown a powerful ability to explore these ubiquitous data, which may be collected from various fields and ...
Chao, Han-Chieh +4 more
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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
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