Results 71 to 80 of about 794 (166)
IET Intelligent Transport Systems, Volume 18, Issue 3, Page 517-527, March 2024.Abstract This study aims to explore the relationship between traffic flow states and crash type/severity in the scenarios of normal crashes, primary crashes, and secondary crashes using the association rules mining approach. The crash data and real‐time traffic data were collected from the I‐880 freeway for five years in California, USA.
Bo Yang +4 more
wiley +1 more source
Theoretical Properties of Closed Frequent Itemsets in Frequent Pattern Mining
MathematicsClosed frequent itemsets (CFIs) play a crucial role in frequent pattern mining by providing a compact and complete representation of all frequent itemsets (FIs).
Huina Zhang +4 more
doaj +1 more source
FCHUIM: Efficient Frequent and Closed High-Utility Itemsets Mining
IEEE Access, 2020 Mining a closed high-utility itemset is a prevalent research task in analyzing transaction databases. However, numerous target itemsets are generated in the closed high-utility itemset mining task.
Tianyou Wei +5 more
doaj +1 more source
The Mining Algorithm of Maximum Frequent Itemsets Based on Frequent Pattern Tree. [PDF]
Comput Intell Neurosci, 2022 Mi X.
europepmc +1 more source
AN EFFICIENT ALGORITHM FOR MINING HIGH UTILITY ITEMSETS
Tạp chí Khoa họcHigh utility itemsets (HUIs) mining is the finding of itemsets that satisfy a user-defined minimum utility threshold. Many successful studies in this field have been carried out, however they are all reliant on Tidset techniques, which records the ...
Nguyen Thi Thanh Thuy*, Nguyen Van Le, Manh Thien Ly
doaj +1 more source
GPU-Accelerated Apriori Algorithm
ITM Web of Conferences, 2017 This paper propose a parallel Apriori algorithm based on GPU (GPUApriori) for frequent itemsets mining, and designs a storage structure using bit table (BIT) matrix to replace the traditional storage mode. In addition, parallel computing scheme on GPU is
Jiang Hao +3 more
doaj +1 more source
New and Efficient Algorithms for Producing Frequent Itemsets with the Map-Reduce Framework
Algorithms, 2018 The Map-Reduce (MR) framework has become a popular framework for developing new parallel algorithms for Big Data. Efficient algorithms for data mining of big data and distributed databases has become an important problem.
Yaron Gonen, Ehud Gudes, Kirill Kandalov
doaj +1 more source
Efficient Top-K Identical Frequent Itemsets Mining without Support Threshold Parameter from Transactional Datasets Produced by IoT-Based Smart Shopping Carts. [PDF]
Sensors (Basel), 2022 Rehman SU +4 more
europepmc +1 more source
A Frequent Itemset Hiding Toolbox [PDF]
, 2019 Advances in data collection and data storage technologies have given way to the establishment of transactional databases among companies and organizations, as they allow enormous amounts of data to be stored efficiently. Useful knowledge can be mined from these data, which can be used in several ways depending on the nature of the data.
Kagklis, Vasileios +2 more
openaire +2 more sources
Class Association Rule Pada Metode Associative Classification
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2011 Frequent patterns (itemsets) discovery is an important problem in associative classification rule mining. Differents approaches have been proposed such as the Apriori-like, Frequent Pattern (FP)-growth, and Transaction Data Location (Tid)-list ...
Eka Karyawati, Edi Winarko
doaj +1 more source