Results 121 to 130 of about 2,597 (181)
Finding Frequent Itemsets in High-Speed Data Streams
, 2008 Finding frequent itemsets from data streams is one of important tasks of stream data mining. In a time-varying data stream, when the significant change on the frequent itemsets is detected, it is ideal to compute the new frequent itemsets as quickly as ...
Xingzhi Sun, Xue Li, Maria E. Orlowska
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Ameliorated Algorithm to Maintain Discovered Frequent Itemsets
It is an important task in data mining to maintain discovered frequent itemsets for association rule mining. Because most time-consuming operation for mining association rules is to find the frequent itemsets from the transaction database.
Makinouchi, Akifumi +5 more
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Mining Recent Frequent Itemsets in Sliding Windows over Data Streams
, 2012 This paper considers the problem of mining recent frequent itemsets over data streams. As the data grows without limit at a rapid rate, it is hard to track the new changes of frequent itemsets over data streams. We propose an efficient one-pass algorithm
Han, Congying, He, Guoping, Xu, Lijun
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Frequent itemset mining on multiprocessor systems.
, 2014 Frequent itemset mining is an important building block in many data mining applications like market basket analysis, recommendation, web-mining, fraud detection, and gene expression analysis. In many of them, the datasets being mined can easily grow up to hundreds of gigabytes or even terabytes of data.
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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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ITL-Mine: Mining Frequent Itemsets More Efficiently
, 2002 The discovery of association rules is an important problem in data mining. It is a two-step process consisting of finding the frequent itemsets and generating association rules from them.
Raj P. Gopalan, Yudho Giri Sucahyo
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A Fuzzy Algorithm for Mining High Utility Rare Itemsets -FHURI
, 2014 Classical frequent itemset mining identifies frequent itemsets in transaction databases using only frequency of item occurrences, without considering utility of items.
Pillai, Jyothi +4 more
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Mining frequent itemsets from uncertain data
, 2007 We study the problem of mining frequent itemsets from uncertain data under a probabilistic framework. We consider transactions whose items are associated with existential probabilities and give a formal definition of frequent patterns under such an ...
Kao, B, Chui, CK, Hung, E
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Extraction of itemsets frequents
International Journal of Mathematics Research, 2020 R. Elayachi +3 more
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