Scalable extraction of timeline information from road traffic data using MapReduce

Imawan, Ardi; Putri, Fadhilah Kurnia; An, Seonga; Jeong, Han-You; Kwon, Joonho

doi:10.1109/dsaa.2015.7344850

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2015

2024

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Cited by 4 publications

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“…There is much need for the replacement of traditional techniques with new big data algorithms. A considerable work was done by A. Imawan et al [26] to extract information from road traffic data using mapreduce. A mapreduce based technique for image processing was proposed by M. Ali and J. Kumar [27].…”

Section: Introductionmentioning

confidence: 99%

A Big Data Solution to Detect Conditional Functional Dependency Violations

Somasekhar¹,

Karthikeyan²

2018

IJET

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The violation detection of conditional functional dependencies in distributed environment has been a research problem giving inspiration to many researchers recently. A very few solutions were given in the recent past to handle conditional functional dependencies. Unfortunately, these are inappropriate in real time big data applications. This article mainly focuses on the big data solution to such type of problems. The proposed IMRCFDHBD algorithm reduces elapsed time and provides scalability with minimum data shipment. The result proves that the algorithm outperforms the state-of-the-art techniques in the big data scenarios.

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Section: Introductionmentioning

confidence: 99%