Results 161 to 170 of about 2,506 (215)

Subset binding enables detection of multimodal patient subgroup patterns and drug target discovery in idiopathic pulmonary fibrosis. [PDF]

Brief Bioinform
Natsume-Kitatani Y, Itoh MN, Takeda Y, Kuroda M, Hirata H, Miyake K, Shiroyama T, Shirai Y, Noda Y, Adachi Y, Enomoto T, Amiya S, Adachi J, Narumi R, Muraoka S, Tomonaga T, Kurohashi S, Cheng F, Tanaka R, Yada S, Aramaki E, Wakamiya S, Chen YA, Fukagawa A, Higuchi C, Nojima Y, Fujiwara T, Nagao C, Takeda T, Matsumura Y, Mizuguchi K, Kumanogoh A, Ueda N.   +32 more
europepmc   +1 more source

Study on urban residents' travel mode choice based on the CART-Apriori method. [PDF]

Sci Rep
Song H, Wang X, Tian W, Shi L, Li S.
europepmc   +1 more source

Leveraging data mining, active learning, and domain adaptation for efficient discovery of advanced oxygen evolution electrocatalysts. [PDF]

Sci Adv
Ding R, Liu J, Hua K, Wang X, Zhang X, Shao M, Chen Y, Chen J.   +7 more
europepmc   +1 more source

Enhancing employee performance appraisal through optimized association rule algorithms: a data mining approach. [PDF]

Sci Rep
Wang J.
europepmc   +1 more source

Advancements in Dental Science through Artificial Intelligence and Machine Learning: A Comprehensive Review. [PDF]

Int J Clin Pediatr Dent
Sharma A, Agarwal N.
europepmc   +1 more source

DecentralDC: Assessing data contribution under decentralized sharing and exchange blockchain. [PDF]

PLoS One
Ke W, Liu Y, Wang J, Fang Z, Chi Z, Guo Y, Wang R, Wang P.   +7 more
europepmc   +1 more source

Optimization algorithm of association rule mining for heavy-haul railway freight train fault data based on distributed parallel computing.

Sci Prog
Bai Y, Li H, Wang W, Liu S, Zhang N, Zhang C.   +5 more
europepmc   +1 more source

Frequent Itemset Mining

, 2019
We present a survey of the most important algorithms that have been proposed in the context of the frequent itemset mining. We start with an introduction and overview of basic sequential algorithms, and then discuss and compare different parallel approaches based on shared-memory, message-passing, map-reduce, and the use of GPU accelerators.
Massimo Cafaro, Marco Pulimeno, Cafaro Massimo   +2 more
exaly   +4 more sources

Some of the next articles are maybe not open access.

Related searches:

Frequent Itemset Mining for Big Data

2013 IEEE International Conference on Big Data, 2013
Frequent Itemset Mining (FIM) is one of the most well known techniques to extract knowledge from data. The combinatorial explosion of FIM methods become even more problematic when they are applied to Big Data. Fortunately, recent improvements in the field of parallel programming already provide good tools to tackle this problem.
Sandy Moens, Emin Aksehirli, Bart Goethals   +2 more
openaire   +2 more sources

Mining Frequent and Homogeneous Closed Itemsets

2016
It is well known that when mining frequent itemsets from a transaction database, the output is usually too large to be effectively exploited by users. To cope with this difficulty, several forms of condensed representations of the set of frequent itemsets have been proposed, among which the notion of closure is one of the most popular.
Inès Hilali, Tao-Yuan Jen, Dominique Laurent 0001, Claudia Marinica, Sadok Ben Yahia   +4 more
openaire   +2 more sources