Results 81 to 90 of about 2,597 (181)
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
Taxonomy-Based Pruning in Generalized Frequent Itemsets Mining [PDF]
, 2012 The original purpose of data mining is for analysis of supermarket transaction data. Now with the rapid development in business, industry and science, data mining is used in lots of domains, so mining interesting information from large database becomes ...
Ma, LinLin
core
Mining Frequent Itemsets in Correlated Uncertain Databases
, 2015 Recently, with the growing popularity of Internet of Things (IoT) and pervasive computing, a large amount of uncertain data, e.g., RFID data, sensor data, real-time video data, has been collected.
Chen, Lei, Tong, Yong Xin, She, Jieying
core +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
Catch the Moment: Maintaining Closed Frequent Itemsets
, 2008 This paper considers the problem of mining closed frequent itemsets over a data stream sliding window using limited memory space. We design a synopsis data structure to monitor transactions in the sliding window so that we can output the current closed
Philip S. Yu +4 more
core
A Further Study in the Data Partitioning Approach
, 2008 Frequent itemsets mining is well explored for various data types, and its computational complexity is well understood. Based on our previous work by Nguyen and Orlowska (2005), this paper shows the extension of the data pre-processing approach to further
Son N. Nguyen +2 more
core
Less frequent itemsets (min. support < 0.40).
, 2018 Less frequent itemsets (min. support < 0.40).
Justin Zhan (5545352) +2 more
core +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