Results 41 to 50 of about 10,108 (225)
Parallel Computation of Rough Set Approximations in Information Systems with Missing Decision Data
Computers, 2018 The paper discusses the use of parallel computation to obtain rough set approximations from large-scale information systems where missing data exist in both condition and decision attributes.
Thinh Cao +4 more
doaj +1 more source
D 3 -MapReduce: Towards MapReduce for Distributed and Dynamic Data Sets [PDF]
, 2015 International audienceSince its introduction in 2004 by Google, MapRe-duce has become the programming model of choice for processing large data sets.
Anjos, Julio +12 more
core +2 more sources
Spatial hotspot detection using polygon propagation
International Journal of Digital Earth, 2019 Spatial scan statistics is one of the most important models in order to detect high activity or hotspots in real world applications such as epidemiology, public health, astronomy and criminology applications on geographic data. Traditional scan statistic
Satya Katragadda +2 more
doaj +1 more source
Enhanced Failure Detection Mechanism in MapReduce
, 2012 The popularity of MapReduce programming model has increased interest in the research community for its improvement. Among the other directions, the point of fault tolerance, concretely the failure detection issue seems to be a crucial one, but that until
Pérez-Hernández, Mar'Ia S. +6 more
core +1 more source
Evaluating MapReduce for seismic data processing using a practical application
Tongxin xuebao, 2012 Huge amounts of seismic data undergo complex iterative processing in the oil industry to get knowledge of the earth’s subsurface structure to detect where oil can be found and recovered.To evaluate the suitability of MapReduce for seismic processing ...
Chang-hai ZHAO +4 more
doaj +2 more sources
A Distributed Approach for High-Dimensionality Heterogeneous Data Reduction
IEEE Access, 2019 The recent explosion of data size in number of records and attributes has triggered the development of a number of Big Data analytics as well as parallel data processing methods and algorithms.
Rania Mkhinini Gahar +3 more
doaj +1 more source
Scalable Computation of Topological Abstractions for Scalar Data
Computer Graphics Forum, EarlyView.Abstract Topological data analysis has become an important tool for large scale scalar data analysis and visualization, efficiently extracting the inherent structure and features of interest of the data. However, with growing dataset sizes and complexity, it is increasingly becoming infeasible to compute topological abstractions of interest in serial ...
M. Will +6 more
wiley +1 more source
A Bibliometric Analysis of Process Mining
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.Process mining studies with numbers. ABSTRACT Process mining (PM) has emerged as a pivotal discipline in data science, bridging traditional process analysis with data‐driven techniques to extract actionable insights from event logs. This study conducts a comprehensive bibliometric analysis of 1764 peer‐reviewed articles from the Web of Science database
Seyfullah Tokumaci +2 more
wiley +1 more source
Applying MapReduce to Conformance Checking
Труды Института системного программирования РАН, 2018 Process mining is a relatively new research field, offering methods of business processes analysis and improvement, which are based on studying their execution history (event logs).
I. S. Shugurov, A. A. Mitsyuk
doaj +1 more source
MapReduce in the Clouds for Science [PDF]
2010 IEEE Second International Conference on Cloud Computing Technology and Science, 2010 The utility computing model introduced by cloud computing combined with the rich set of cloud infrastructure services offers a very viable alternative to traditional servers and computing clusters. MapReduce distributed data processing architecture has become the weapon of choice for data-intensive analyses in the clouds and in commodity clusters due ...
Thilina Gunarathne +3 more
openaire +1 more source