Results 81 to 90 of about 9,218 (205)
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
Data‐Driven Materials Research and Development for Functional Coatings
Advanced Science, Volume 11, Issue 42, November 13, 2024.Functional coatings play a vital role in various industries for their protective and functional properties. However, its design often involves time‐consuming experimentation with multiple materials and processing parameters. To overcome these limitations, data‐driven approaches are gaining traction in materials science. This review provides an overview
Kai Xu +8 more
wiley +1 more source
Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach
Journal of ICT Research and Applications, 2013 Mining frequent patterns in large transactional databases is a highly researched area in the field of data mining. Existing frequent pattern discovering algorithms suffer from many problems regarding the high memory dependency when mining large amount of
A. V. Senthil Kumar, R. S. D. Wahidabanu
doaj
An association rule-based approach for frequent item mining of multi-stage access data
Discover ComputingThe processing of large-scale datasets is complex and requires high efficiency. The database needs to be scanned multiple times by traditional Apriori algorithms to generate candidate itemsets, resulting in significantly reduced efficiency, but also have
Silong Wu
doaj +1 more source
Frequent Itemsets Mining With Differential Privacy Over Large-Scale Data
IEEE Access, 2018 Frequent itemsets mining with differential privacy refers to the problem of mining all frequent itemsets whose supports are above a given threshold in a given transactional dataset, with the constraint that the mined results should not break the privacy ...
Xinyu Xiong +6 more
doaj +1 more source
Mining frequent itemsets from streaming transaction data using genetic algorithms
Journal of Big Data, 2020 This paper presents a study of mining frequent itemsets from streaming data in the presence of concept drift. Streaming data, being volatile in nature, is particularly challenging to mine.
Sikha Bagui, Patrick Stanley
doaj +1 more source
AGING MEDICINE, Volume 7, Issue 5, Page 543-552, October 2024.Factors significantly associated with physical activity outcomes in people with dementia in the final regression models. The figure highlights that psychosocial factors are associated with different constructs related to physical activity. Only the presence of intrapersonal barriers to physical activity was associated with both total physical activity ...
Nicolas Farina +5 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