Results 81 to 90 of about 846,106 (226)
arules - A Computational Environment for Mining Association Rules and Frequent Item Sets [PDF]
Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases.
Bettina Grün +2 more
core
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
Content Validity of Creativity Self‐Report Questionnaires From PISA 2022
The Journal of Creative Behavior, Volume 59, Issue 2, June 2025.ABSTRACT The present paper questions the content validity of the eight creativity‐related self‐report scales available in PISA 2022's context questionnaire and provides a set of considerations for researchers interested in using these indexes. Specifically, we point out some threats to the content validity of these scales (e.g., creative thinking self ...
B. Goecke, S. Weiss, B. Barbot
wiley +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
Mining Frequent Closed Itemsets with the Frequent Pattern List
, 2008 The mining of the complete set of frequent itemsets will lead to a huge number of itemsets. Fortunately, this problem can be reduced to the mining of frequent closed itemsets (FCIs), which results in a much smaller number of itemsets.
Ching-chi Hsu +2 more
core
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
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
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
Less frequent itemsets (min. support < 0.40).
, 2018 Less frequent itemsets (min. support < 0.40).
Justin Zhan (5545352) +2 more
core +1 more source