Results 151 to 160 of about 36,780 (203)

Selective ensemble method for anomaly detection based on parallel learning. [PDF]

Sci Rep
Liu Y, Zhu L, Ding L, Huang Z, Sui H, Wang S, Song Y.   +6 more
europepmc   +1 more source

Improved security for IoT-based remote healthcare systems using deep learning with jellyfish search optimization algorithm. [PDF]

Sci Rep
Kateb F, Ragab M, Abukhodair F, Abdulkader OA, Maghrabi LA, Binyamin SS, Al-Hanawi MK.   +6 more
europepmc   +1 more source

A novel intrusion detection framework using hybrid deep learning to detect IIoT cloud environments attacks. [PDF]

Sci Rep
Chen S, Feng X.
europepmc   +1 more source

Incremental MapReduce Computations [PDF]

, 2014
openaire   +1 more source

Leveraging hybrid model for accurate sentiment analysis of Twitter data. [PDF]

Sci Rep
Jonnala NS, Ram Teja AVS, Rajeswari SR, Jakeer S, Dheeraj A, Bansal S, Prakash K, Singh S, Faruque MRI, Al-Mugren KS.   +9 more
europepmc   +1 more source

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MapReduce

Communications of the ACM, 2008
MapReduce is a programming model and an associated implementation for processing and generating large datasets that is amenable to a broad variety of real-world tasks. Users specify the computation in terms of a map and a reduce function, and the underlying runtime system automatically ...
Jeffrey Dean, Sanjay Ghemawat
exaly   +2 more sources

Cross-MapReduce: Data transfer reduction in geo-distributed MapReduce

Future Generation Computer Systems, 2021
Abstract The MapReduce model is widely used to store and process big data in a distributed manner. MapReduce was originally developed for a single tightly coupled cluster of computers. Approaches such as Hierarchical and Geo-Hadoop are designed to address geo-distributed MapReduce processing.
Abdorreza Savadi, Mahmoud Naghibzadeh
exaly   +2 more sources

MapReduce

2011
. Map/Reduce
David Padua, Amol Ghoting, John A. Gunnels, Mark S. Squillante, José Meseguer, James H. Cownie, Duncan Roweth, Sarita V. Adve, Hans J. Boehm, Sally A. McKee, Robert W. Wisniewski, George Karypis, Allen D. Malony, Steven Gottlieb, Rolf Riesen, Arthur B. Maccabe, Gianfranco Bilardi, Andrea Pietracaprina, Arun Kejariwal, Alexandru Nicolau, Christian Lengauer, John L. Gustafson, William Gropp, Jean-Pierre Prost, David Padua, Geoff Lowney, Patrick Amestoy, Alfredo Buttari, Iain Duff, Abdou Guermouche, Jean-Yves L’Excellent, Bora Uçar, Robert H. Halstead, Mario Nemirovsky, Patrick Amestoy, Alfredo Buttari, Iain Duff, Abdou Guermouche, Jean-Yves L’Excellent, Bora Uçar, Scott Pakin   +40 more
  +4 more sources

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

MapReduce

Communications of the ACM, 2010
MapReduce advantages over parallel databases include storage-system independence and fine-grain fault tolerance for large jobs.
Jeffrey Dean, Sanjay Ghemawat
openaire   +1 more source