Results 111 to 120 of about 1,488,747 (207)

Algorithms for Extracting Frequent Episodes in the Process of Temporal Data Mining [PDF]

An important aspect in the data mining process is the discovery of patterns having a great influence on the studied problem. The purpose of this paper is to study the frequent episodes data mining through the use of parallel pattern discovery algorithms.
Alexandru PIRJAN
core  

DIAFM: An Improved and Novel Approach for Incremental Frequent Itemset Mining

Mathematics
Traditional approaches to data mining are generally designed for small, centralized, and static datasets. However, when a dataset grows at an enormous rate, the algorithms become infeasible in terms of huge consumption of computational and I/O resources.
Mohsin Shaikh, Sabina Akram, Jawad Khan, Shah Khalid, Youngmoon Lee   +4 more
doaj   +1 more source

FraudMiner: a novel credit card fraud detection model based on frequent itemset mining. [PDF]

ScientificWorldJournal, 2014
Seeja KR, Zareapoor M, Zareapoor M.
europepmc   +1 more source

Unravelling associations between unassigned mass spectrometry peaks with frequent itemset mining techniques. [PDF]

Proteome Sci, 2014
Vu TN, Mrzic A, Valkenborg D, Maes E, Lemière F, Goethals B, Laukens K.   +6 more
europepmc   +1 more source

Uncertainty-Aware Contamination Detection in IoT Water Networks via Interval Type-2 Fuzzy Rare Itemset Mining. [PDF]

Sensors (Basel)
Mariadhason JS, Joseph ER, Srinivasan P, Francis RD.   +3 more
europepmc   +1 more source

Best-first search-based approach for mining top-k closed frequent itemsets from uncertain databases. [PDF]

PLoS One
Le N, Vo H, Nguyen T.
europepmc   +1 more source

Genetic Programming and Frequent Itemset Mining to Identify Feature Selection Patterns of iEEG and fMRI Epilepsy Data. [PDF]

Eng Appl Artif Intell, 2015
Smart O, Burrell L.
europepmc   +1 more source

Evidence-based precision in TCM: A systematic review and Meta-Analysis of data mining for syndrome-specific acupoint combinations in acute asthma exacerbations. [PDF]

Medicine (Baltimore)
Yang S, Yang Y, Ding Y, Liu X.
europepmc   +1 more source

SiBIC: a web server for generating gene set networks based on biclusters obtained by maximal frequent itemset mining. [PDF]

PLoS One, 2013
Takahashi K, Takigawa I, Mamitsuka H.
europepmc   +1 more source

Reduction of Erasable Itemset Mining to Frequent Itemset Mining

Proceedings of the Annual Conference of JSAI, 2019
HONG, Tzung-Pei, WANG, Chun-Ho, LI, Chia-Che, LIN, Wen-Yang   +3 more
openaire   +1 more source