Results 121 to 130 of about 659,904 (212)

A primer to frequent itemset mining for bioinformatics. [PDF]

Brief Bioinform, 2015
Naulaerts S, Meysman P, Bittremieux W, Vu TN, Vanden Berghe W, 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

An effectiveness assessment ensemble for transmission corridor mechanized construction schemes based on weighted itemset mining and factor criticality analysis. [PDF]

Sci Rep
Yang X, Hu J, Sun C, Huang Y, Tang C, Huang J.   +5 more
europepmc   +1 more source

Incremental high average-utility itemset mining: survey and challenges. [PDF]

Sci Rep
Chen J, Yang S, Ding W, Li P, Liu A, Zhang H, Li T.   +6 more
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

CisMiner: genome-wide in-silico cis-regulatory module prediction by fuzzy itemset mining. [PDF]

PLoS One, 2014
Navarro C, Lopez FJ, Cano C, Garcia-Alcalde F, Blanco A.   +4 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

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

Mining Approximate Frequent Itemset from Noisy Data

, 2005
Frequent itemset mining is a popular and important first step in analyzing data sets across a broad range of applications. The traditional, “exact ” approach for finding frequent itemsets requires that every item in the itemset occurs in each supporting ...
Susan Paulsen, Andrew Nobel, Wei Wang, Jan Prins, Jinze Liu   +4 more
core  

A pattern-growth approach for mining maximal fault-tolerant frequent itemsets. [PDF]

Sci Rep
Bashir S.
europepmc   +1 more source