Results 71 to 80 of about 1,488,747 (207)
Mining frequent itemsets a perspective from operations research [PDF]
Many papers on frequent itemsets have been published. Besides somecontests in this field were held. In the majority of the papers the focus ison speed. Ad hoc algorithms and datastructures were introduced.
Kosters, W.A., Pijls, W.H.L.M.
core
Background Middle‐aged and older adults with severe mental illness (SMI) often experience a higher burden of multiple chronic conditions compared with the general population. Despite this, limited research has explored how these conditions cluster and interact, particularly in social settings where integrated mental and physical healthcare remains ...
Yue-Hui Yu, Ya-Xuan Mao, Quan Lu
wiley +1 more source
Identifying the Focus Word in Natural Language Questions Based on Association Rules
Knowledge base‐based intelligent question‐answering systems have insufficient understanding of the questions. In the early stages of research, it is effective in most cases that the existing natural language question‐understanding methods can answer questions by connecting entities and relationships when ignoring the identification of focus words ...
Xin Hu +5 more
wiley +1 more source
Frequent Itemset Mining for Big Data Using Greatest Common Divisor Technique
The discovery of frequent itemsets is one of the very important topics in data mining. Frequent itemset discovery techniques help in generating qualitative knowledge which gives business insight and helps the decision makers. In the Big Data era the need
Mohamed A. Gawwad +2 more
doaj +1 more source
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
ABSTRACT Machine learning techniques are increasingly used for high‐stakes decision‐making, such as college admissions, loan attribution, or recidivism prediction. Thus, it is crucial to ensure that the models learnt can be audited or understood by human users, do not create or reproduce discrimination or bias and do not leak sensitive information ...
Julien Ferry +4 more
wiley +1 more source
ABSTRACT Background and Aims Infertility, as defined by the World Health Organization, is the inability to conceive after 12 months of regular, unprotected intercourse. This study aimed to identify factors influencing infertility by applying data mining techniques, specifically rule‐mining methods, to analyze diverse patient data and uncover relevant ...
Hosna Heydarian +3 more
wiley +1 more source
Association rules recommendation algorithm supporting recommendation nonempty
Existing association rule recommendation technologies were focus on extraction efficiency of association rule in data mining.However,it lacked consideration of recommendation balance between popular and unusual data and efficient processing.In order to ...
Ming HE, Wei-shi LIU, Jiang ZHANG
doaj +2 more sources
Research on Frequent Itemset Mining of Imaging Genetics GWAS in Alzheimer's Disease. [PDF]
Liang H +7 more
europepmc +1 more source
TKFIM: Top-K frequent itemset mining technique based on equivalence classes. [PDF]
Iqbal S +5 more
europepmc +1 more source

