Results 91 to 100 of about 719,228 (260)

An Evolutionary Algorithm to Mine High-Utility Itemsets

Advances in Electrical and Electronic Engineering, 2015
High-utility itemset mining (HUIM) is a critical issue in recent years since it can be used to reveal the profitable products by considering both the quantity and profit factors instead of frequent itemset mining (FIM) of association rules (ARs). In this
Jerry Chun-Wei Lin, Lu Yang, Philippe Fournier-Viger, Jaroslav Frnda, Lukas Sevcik, Miroslav Voznak   +5 more
doaj   +1 more source

Electric vehicle load forecasting based on convolutional networks with attention mechanism and federated learning method

IET Generation, Transmission &Distribution, Volume 18, Issue 13, Page 2313-2324, July 2024.
This paper proposes an electric vehicle (EV) load diagnosis algorithm considering data privacy. The validity of the algorithm in this paper is verified by using the real collected EV load data. Abstract Accurate forecasting of electric vehicle (EV) load is essential for grid stability and energy management. EV load forecasting is influenced by multiple
Ruien Bian, Long Wang, Yadong Liu, Zhou Dai   +3 more
wiley   +1 more source

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, Philippe Fournier-Viger, Ji Zhang   +2 more
doaj   +1 more source

Reconstructing thicket clump formation using association rules analysis

Journal of Vegetation Science, Volume 35, Issue 3, May/June 2024.
Association rules (or market basket) analysis was effective in eliciting common associations between species and size classes across different stages of thicket clump formation in a savanna. Vachellia karroo established alone in open grassland, whereas a suite of clump‐initiating species recruited in close association with large V.
Rhys Nell, Tiffany Pillay, Susanne Vetter   +2 more
wiley   +1 more source

Graph-based biomedical text summarization: An itemset mining and sentence clustering approach

Journal of Biomedical Informatics, 2018
OBJECTIVE Automatic text summarization offers an efficient solution to access the ever-growing amounts of both scientific and clinical literature in the biomedical domain by summarizing the source documents while maintaining their most informative ...
Mozhgan Nasr Azadani, Nasser Ghadiri, Ensieh Davoodijam   +2 more
semanticscholar   +1 more source

Datasets for Itemset, Sequence and Tree Mining

, 2020
There are three different datasets included, that can be used for itemset, sequence and tree mining methods. dense_db.zip contains various real itemset datasets like chess, connect, mushroom, pumsb, T10I4D100K, T40I10D100K and so on, used in the papers
Zaki, Mohammed J
core   +1 more source

An efficient and resilience linear prefix approach for mining maximal frequent itemset using clustering

Journal of Safety Science and Resilience
The numerous volumes of data generated every day necessitate the deployment of new technologies capable of dealing with massive amounts of data efficiently.
M. Sinthuja, S. Pravinthraja, B K Dhanalakshmi, H L Gururaj, Vinayakumar Ravi, G Jyothish Lal   +5 more
doaj   +1 more source

Closed frequent itemset mining with arbitrary side constraints [PDF]

, 2018
Frequent itemset mining (FIM) is a method for finding regularities in transaction databases. It has several application areas, such as market basket analysis, genome analysis, and drug design. Finding frequent itemsets allows further analysis to focus on
Nightingale, Peter William, Ozgur Akgun, Kocak, Gokberk, Peter Nightingale, Gokberk Kocak, Akgun, Ozgur, Miguel, Ian James, Ian Miguel   +7 more
core   +1 more source

Research on Frequent Itemset Mining of Imaging Genetics GWAS in Alzheimer's Disease. [PDF]

Genes (Basel), 2022
Liang H, Cao L, Gao Y, Luo H, Meng X, Wang Y, Li J, Liu W.   +7 more
europepmc   +1 more source

Accelerating Parallel Frequent Itemset Mining on Graphics Processors with Sorting

, 2013
Part 4: Session 4: Multi-core Computing and GPUInternational audienceFrequent Itemset Mining (FIM) is one of the most investigated fields of data mining.
Hsu, Ching-Hsien, Ching-Hsien Hsu, Yu, Kun-Ming, Liu, Sheng-Hui, Huang, Yuan-Shao, Zhou, Li-Wei, Li-Wei Zhou, Yuan-Shao Huang, Kun-Ming Yu, Sheng-Hui Liu   +9 more
core   +1 more source