Results 121 to 130 of about 2,506 (215)

Frequent itemset mining on multiprocessor systems

, 2013
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.
Schlegel, Benjamin
core  

Result Integrity Verification of Outsourced Frequent Itemset Mining

, 2013
Part 7: Short PapersInternational audienceThe data-mining-as-a-service (DMaS) paradigm enables the data owner (client) that lacks expertise or computational resources to outsource its mining tasks to a third-party service provider (server).
Hui Wang, Liu, Ruilin, Boxiang Dong, Wang, Hui,, Ruilin Liu, Dong, Boxiang   +5 more
core   +1 more source

Improved Algorithm for Frequent Itemsets Mining Based on Apriori and FP-Tree

, 2013
Frequent itemset mining plays an important role in association rule mining.
Priti Chandra, B.L.Deekshatulu, Dr. Sujatha Dandu   +2 more
core  

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

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

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

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

CLTD-LP: an optimized top-down clustering approach with linear prefix trees for scalable frequent pattern discovery in large datasets. [PDF]

Sci Rep
Sinthuja M, Diviya M, Saranya P.
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