Results 101 to 110 of about 9,218 (205)
IEEE AccessTraditional pattern mining algorithms are based on tree and linked list structures. However, they often only consider a single factor of frequency or utility and have to deal with exponential search spaces as well as generate numerous candidates.
Xiumei Zhao, Xincheng Zhong, Bing Han
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A Mining-Based Compression Approach for Constraint Satisfaction Problems
, 2013 In this paper, we propose an extension of our Mining for SAT framework to Constraint satisfaction Problem (CSP). We consider n-ary extensional constraints (table constraints). Our approach aims to reduce the size of the CSP by exploiting the structure of
Jabbour, Said +2 more
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An efficient pattern growth approach for mining fault tolerant frequent itemsets. [PDF]
Expert Syst Appl, 2020 Bashir S, Bashir S.
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Grafting for Combinatorial Boolean Model using Frequent Itemset Mining
, 2017 This paper introduces the combinatorial Boolean model (CBM), which is defined as the class of linear combinations of conjunctions of Boolean attributes. This paper addresses the issue of learning CBM from labeled data.
Lee, Taito +2 more
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FREQUENT ITEMSETS MINING FOR BIG DATA
, 2019 Frequent Itemsets Mining (FIM) is a fundamental mining model and plays an important role in Data Mining. It has a vast range of application fields and can be employed as a key calculation phase in many other mining models such as Association Rules, Correlations, Classifications, etc. Generally speaking, FIM counts the frequencies of co-occurrence items,
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IEEE AccessData analytics is an integral part of strategic decision making in various fields but not limited to business, education and healthcare systems. Existing research works focus on the discovery of itemsets with rare antecedents and consequent or frequent ...
Shwetha Rai +4 more
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Extraction of itemsets frequents
International Journal of Mathematics Research, 2020 R. Elayachi +3 more
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Probabilistic Support Prediction: Fast Frequent Itemset Mining in Dense Data
IEEE AccessFrequent itemset mining (FIM) is a highly resource-demanding data-mining task fundamental to numerous data-mining applications. Support calculation is a frequently performed computation-intensive operation of FIM algorithms, whereas storing transactional
Muhammad Sadeequllah +3 more
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Application of frequent itemsets mining to analyze patterns of one-stop visits in Taiwan. [PDF]
PLoS One, 2011 Tu CY, Chen TJ, Chou LF.
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Mining personalized core traditional Chinese medicine prescriptions for rheumatoid arthritis and elucidating their mechanisms via frequent closed Itemset compression and multilevel network pharmacology. [PDF]
Front Mol BiosciChen X +11 more
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