To explore the data processing of high-speed railway fault signal diagnosis based on
MapReduce algorithm, the partitioning strategy of data flow was improved, and Bias …

Recently, increasingly large amounts of data are generated from a variety of sources.
Existing data processing technologies are not suitable to cope with the huge amounts of …

MapReduce (MR) computing paradigm and its open source implementation Hadoop have
become a de facto standard to process big data in a distributed environment. Initially, the …

BigGraph applications have been mostly implemented with large-scale parallel processing
frameworks based on MapReduce. However, it continues to be challenging to meet their …

Mining information from web pages to automatically determine the acronym and its
expansion is an important and challenging task. It is considered not easy to do because the …

Reachability testing is an important approach to testing concurrent programs. It generates
and executes all the possible sequences of a concurrent program automatically with a given …

This research proposed a parallelized approach to scaling up the calculation of inundation
height, the minimum sea‐level rise required to inundate a cell on a digital elevation model …

O agrupamento de dados (ou do inglês Clustering) é uma tarefa não supervisionada capaz
de descrever objetos em grupos (ou clusters), de maneira que objetos de um mesmo grupo …

Distributed system consists of networked computers that provide a coherent system view to
its users. Distributed computing is the use of distributed system to solve complex …

Hadoop MapReduce is the community accepted platform that deals with the gigantic data in
an efficient and cost-effective manner. To cope up with ever growing datasets and shrinking …