Results 11 to 20 of about 36,780 (203)
Big Data Technology Fusion Back Propagation Neural Network in Product Innovation Design Method
IET Networks, Accepted Article., 2022 This research uses big data technology to combine the process of product innovation design method, which has certain significance for the formation of intelligent and systematic product innovation design method. Meanwhile, while predicting the results of all products innovative design methods, it can improve the product's predictive innovative design ...
Ren Li, Qiang Zeng
wiley +1 more source
Garbage collection auto-tuning for Java MapReduce on Multi-Cores [PDF]
, 2011 MapReduce has been widely accepted as a simple programming pattern that can form the basis for efficient, large-scale, distributed data processing. The success of the MapReduce pattern has led to a variety of implementations for different computational ...
Allen E. +10 more
core +1 more source
Efficient Multi-way Theta-Join Processing Using MapReduce [PDF]
, 2012 Multi-way Theta-join queries are powerful in describing complex relations and therefore widely employed in real practices. However, existing solutions from traditional distributed and parallel databases for multi-way Theta-join queries cannot be easily ...
Chen, Lei, Wang, Min, Zhang, Xiaofei
core +3 more sources
Recognizing Indonesian Acronym and Expansion Pairs with Supervised Learning and MapReduce
Information, 2020 During the previous decades, intelligent identification of acronym and expansion pairs from a large corpus has garnered considerable research attention, particularly in the fields of text mining, entity extraction, and information retrieval.
Taufik Fuadi Abidin +4 more
doaj +1 more source
REST-MapReduce: An Integrated Interface but Differentiated Service
Journal of Applied Mathematics, 2014 With the fast deployment of cloud computing, MapReduce architectures are becoming the major technologies for mobile cloud computing. The concept of MapReduce was first introduced as a novel programming model and implementation for a large set of ...
Jong-Hyuk Park +3 more
doaj +1 more source
Proving Equivalence Between Imperative and MapReduce Implementations Using Program Transformations [PDF]
Electronic Proceedings in Theoretical Computer Science, 2018 Distributed programs are often formulated in popular functional frameworks like MapReduce, Spark and Thrill, but writing efficient algorithms for such frameworks is usually a non-trivial task.
Bernhard Beckert +5 more
doaj +1 more source
On using MapReduce to scale algorithms for Big Data analytics: a case study
Journal of Big Data, 2019 Introduction Many data analytics algorithms are originally designed for in-memory data. Parallel and distributed computing is a natural first remedy to scale these algorithms to “Big algorithms” for large-scale data.
Phongphun Kijsanayothin +2 more
doaj +1 more source
Cloudgene: A graphical execution platform for MapReduce programs on private and public clouds
BMC Bioinformatics, 2012 Background The MapReduce framework enables a scalable processing and analyzing of large datasets by distributing the computational load on connected computer nodes, referred to as a cluster.
Schönherr Sebastian +5 more
doaj +1 more source
Parallel Processing of Large Graphs [PDF]
, 2013 More and more large data collections are gathered worldwide in various IT systems. Many of them possess the networked nature and need to be processed and analysed as graph structures.
Indyk, Wojciech +2 more
core +1 more source
Algorithms, 2021 Microwave imaging systems are currently being investigated for breast cancer, brain stroke and neurodegenerative disease detection due to their low cost, portable and wearable nature. At present, commonly used radar-based algorithms for microwave imaging
Rahmat Ullah, Tughrul Arslan
doaj +1 more source