Results 21 to 30 of about 36,780 (203)
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
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ICTACT Journal on Soft Computing, 2022 Hierarchical Data mining using distributed environment is an imperative in big data analysis. Multilevel association rules can provide more substantial information than single level rules, and it also determines hierarchical knowledge from the dataset ...
Dinesh J. Prajapati
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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
Full Support for Efficiently Mining Multi-Perspective Declarative Constraints from Process Logs
Information, 2019 Declarative process management has emerged as an alternative solution for describing flexible workflows. In turn, the modelling opportunities with languages such as Declare are less intuitive and hard to implement.
Christian Sturm +2 more
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Big data cleaning modeling of operation status of coal mine fully—mechanized coal mining equipment
Gong-kuang zidonghua, 2018 In view of problems of large amount of data and noise and missing values existed in data of operation status of coal mine fully—mechanized coal mining equipment, a big data cleaning model of operation status of coal mine fully—mechanized coal mining ...
MA Hongwei +4 more
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Locality-Aware Hybrid Coded MapReduce for Server-Rack Architecture
, 2017 MapReduce is a widely used framework for distributed computing. Data shuffling between the Map phase and Reduce phase of a job involves a large amount of data transfer across servers, which in turn accounts for increase in job completion time.
Gupta, Sneh, Lalitha, V.
core +1 more source
Enumerating Maximal Bicliques from a Large Graph using MapReduce [PDF]
, 2014 We consider the enumeration of maximal bipartite cliques (bicliques) from a large graph, a task central to many practical data mining problems in social network analysis and bioinformatics. We present novel parallel algorithms for the MapReduce platform,
Mukherjee, Arko +2 more
core +4 more sources
Embed and Conquer: Scalable Embeddings for Kernel k-Means on MapReduce [PDF]
, 2014 The kernel $k$-means is an effective method for data clustering which extends the commonly-used $k$-means algorithm to work on a similarity matrix over complex data structures.
Elgohary, Ahmed +3 more
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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
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Computing marginals using MapReduce [PDF]
Journal of Computer and System Sciences, 2018 We consider the problem of computing the data-cube marginals of a fixed order $k$ (i.e., all marginals that aggregate over $k$ dimensions), using a single round of MapReduce. The focus is on the relationship between the reducer size (number of inputs allowed at a single reducer) and the replication rate (number of reducers to which an input is sent ...
Afrati, Foto N. +3 more
openaire +3 more sources