Results 41 to 50 of about 8,833 (199)
DiffNodesets: An Efficient Structure for Fast Mining Frequent Itemsets
, 2015 Mining frequent itemsets is an essential problem in data mining and plays an important role in many data mining applications. In recent years, some itemset representations based on node sets have been proposed, which have shown to be very efficient for ...
Deng, Zhi-Hong
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Proof Learning in PVS With Utility Pattern Mining
IEEE Access, 2020 Interactive theorem provers (ITPs) are software tools that allow human users to write and verify formal proofs. In recent years, an emerging research area in ITPs is proof mining, which consists of identifying interesting proof patterns that can be used ...
M. Saqib Nawaz +2 more
doaj +1 more source
A log mining approach for process monitoring in SCADA [PDF]
, 2012 SCADA (Supervisory Control and Data Acquisition) systems are used for controlling and monitoring industrial processes. We propose a methodology to systematically identify potential process-related threats in SCADA. Process-related threats take place when
Bolzoni, Damiano +2 more
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Generic Itemset Mining Based on Reinforcement Learning
IEEE Access, 2022 One of the biggest problems in itemset mining is the requirement of developing a data structure or algorithm, every time a user wants to extract a different type of itemsets.
Kazuma Fujioka, Kimiaki Shirahama
doaj +1 more source
Efficient Analysis of Pattern and Association Rule Mining Approaches
, 2014 The process of data mining produces various patterns from a given data source. The most recognized data mining tasks are the process of discovering frequent itemsets, frequent sequential patterns, frequent sequential rules and frequent association rules.
Lazzez, Amor, Slimani, Thabet
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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
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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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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
doaj +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
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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