Results 171 to 180 of about 10,108 (225)

LS-BMO-HDBSCAN as a hybrid memetic bacterial intelligence framework for efficient data clustering. [PDF]

Sci Rep
Al-Nussairi AKJ, Abdulazez AA, Hadi AA, Malik S, Patro SGK, Mahanty C, Alamiery AA, Naveed QN, Khan S, Zewude A.   +9 more
europepmc   +1 more source

DANI: fast diffusion aware network inference with preserving topological structure property. [PDF]

Sci Rep
Ramezani M, Ahadinia A, Farhadi E, Rabiee HR.   +3 more
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

The analysis of aerobics intelligent fitness system for neurorobotics based on big data and machine learning. [PDF]

Heliyon
Liu Y, Cao S.
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

A dataset on the use of online video by students at the in-video level. [PDF]

Data Brief
Córcoles C, Rodríguez GC, Guerrero-Roldán AE, Huertas MA.   +3 more
europepmc   +1 more source

BSP vs MapReduce

Procedia Computer Science, 2012
13 pages, appeared at ICCS ...
Matthew Felice Pace, Pace, Matthew Felice   +1 more
exaly   +4 more sources

A New Approach to the Cloud-Based Heterogeneous MapReduce Placement Problem

IEEE Transactions on Services Computing, 2016
Guaranteeing Quality of Service (QoS) with minimum computation cost is the most important objective of cloud-based MapReduce computations. Minimizing the total computation cost of cloud-based MapReduce computations is done through MapReduce placement ...
Maolin Tang
exaly   +2 more sources

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Tuple MapReduce: Beyond Classic MapReduce

2012 IEEE 12th International Conference on Data Mining, 2012
This paper proposes Tuple Map Reduce, a new foundational model extending Map Reduce with the notion of tuples. Tuple Map Reduce allows to bridge the gap between the low-level constructs provided by Map Reduce and higher-level needs required by programmers, such as compound records, sorting or joins.
Pedro Ferrera, Ivan de Prado, Eric Palacios, Jose Luis Fernandez-Marquez, Giovanna Di Marzo Serugendo   +4 more
openaire   +1 more source

An Advanced MapReduce: Cloud MapReduce, Enhancements and Applications

IEEE Transactions on Network and Service Management, 2014
Recently, Cloud Computing is attracting great attention due to its provision of configurable computing resources. MapReduce (MR) is a popular framework for data-intensive distributed computing of batch jobs. MapReduce suffers from the following drawbacks: 1. It is sequential in its processing of Map and Reduce Phases 2.
Devendra Dahiphale, Rutvik Karve, Athanasios V. Vasilakos, Huan Liu, Zhiwei Yu, Amit Chhajer, Jianmin Wang 0001, Chaokun Wang   +7 more
openaire   +1 more source