Analysis of Multidimensional Data with High Dimensionality: Data Access Problems and Possible Solutions

Borodin, Andrey; Mirvoda, Sergey; Porshnev, Sergey

doi:10.1051/itmconf/20160801005

Cited by 4 publications

(1 citation statement)

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“…Beside the complex processing of geospatial data, a considerable amount of work has been done on use of multidimensional data structures in information processing systems (IPS), the applications of which have been in fields of business analysis, astronomy, geomatics, bioinformatics, etc. [9]. The term "Multidimensional" essentially describes the way in which numerical information can be categorized and viewed [16].…”

Section: Big-geospatial Data Processingmentioning

confidence: 99%

Multi-dimensional geospatial data mining in a distributed environment using MapReduce

Alkathiri

Abdul²,

Potdar³

2019

J Big Data

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Data mining and machine learning techniques for processing raster data consider a single spectral band of data at a time. The individual results are combined to obtain the final output. The essence of related multi-spectral information is lost when the bands are considered independently. The proposed platform is based on Apache Hadoop ecosystem and supports performing analysis on large amounts of multispectral raster data using MapReduce. A novel technique of transforming the spectral space to the geometrical space is also proposed. The technique allows to consider multiple bands coherently. The results of clustering 10 6 pixels for multiband imagery with widely used GIS software have been tested and other machine learning methods are planned to be incorporated in the platform. The platform is scalable to support tens of spectral bands. The results from our platform were found to be better and are also available faster due to application of distributed processing.

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Section: Big-geospatial Data Processingmentioning

confidence: 99%