Results 21 to 30 of about 10,119 (225)
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
Large-scale Parallel Stratified Defeasible Reasoning [PDF]
, 2012 We are recently experiencing an unprecedented explosion of available data from the Web, sensors readings, scientific databases, government authorities and more.
Tachmazidis, Ilias +5 more
core +1 more source
Six Pass MapReduce Implementation of Strassen's Algorithm for Matrix Multiplication [PDF]
, 2018 Click on the DOI link to access the article (may not be free).Consider the multiplication of two n x n matrices. A straight-forward sequential algorithm for computing the product takes Θ(n3) time.
Ramanan, Prakash, Prakash Ramanan
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Comparative Study Parallel Join Algorithms for MapReduce environment
Труды Института системного программирования РАН, 2018 There are the following techniques that are used to analyze massive amounts of data: MapReduce paradigm, parallel DBMSs, column-wise store, and various combinations of these approaches. We focus in a MapReduce environment.
A. Yu. Pigul
doaj +1 more source
Building cubes with MapReduce [PDF]
Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP, 2011 In the last years, the problems of using generic storage techniques for very specific applications has been detected and outlined. Thus, some alternatives to relational DBMSs (e.g., BigTable) are blooming. On the other hand, cloud computing is already a reality that helps to save money by eliminating the hardware as well as software fixed costs and ...
Alberto Abelló +2 more
openaire +1 more source
Adaptive Combiner for MapReduce on cloud computing [PDF]
, 2014 MapReduce is a programming model to process a massive amount of data on cloud computing. MapReduce processes data in two phases and needs to transfer intermediate data among computers between phases. MapReduce allows programmers to aggregate intermediate
Lee, Wei-Tsong
core +1 more source
Collaborative Mappers based on Co-evolutionary Optimization Technique in MapReduce
International Journal of Information and Communication Technology Research, 2022 MapReduce algorithm inspired by the map and reduces functions commonly used in functional programming. The use of this model is more beneficial when optimization of the distributed mappers in the MapReduce framework comes into the account.
Mohammad Reza Ahmadi, Davood Maleki
doaj
Big Data Analytics in Online Structural Health Monitoring
International Journal of Prognostics and Health Management, 2016 This manuscript explores the application of big data analytics in online structural health monitoring. As smart sensor technology is making progress and low cost online monitoring is increasingly possible, large quantities of highly heterogeneous data ...
Guowei Cai, Sankaran Mahadevan
doaj +1 more source
Efficient Computation of the Well-Founded Semantics over Big Data [PDF]
, 2014 Data originating from theWeb, sensor readings and social media result in increasingly huge datasets. The so called Big Data comes with new scientific and technological challenges while creating new opportunities, hence the increasing interest in academia
Faber, Wolfgang +2 more
core +1 more source
Verifica Sperimentale di un modello per MapReduce [PDF]
, 2022 Proposto nel 2005 a partire dall'esperienza implementativa di Google, MapReduce rappresenta a tutt'oggi uno dei più utilizzati paradigmi per il calcolo parallelo.
Rodeghiero, Paolo
core