Big data environment for geospatial data analysis

In the big data environment, the visualization technique has been increasingly adopted to mine the data on library and information (L&I), with the diversification of data sources and the growth of data volume. The previous research into the information association of L&I visualization network rarely tries to construct such a network or explore the information association of the network. To overcome these defects, this paper explores the visualization of L&I from the perspective of big data analysis and fusion. Firstly, the authors analyzed the topology of the L&I visualization network and calculated the metrics for the construction of L&I visualization topology map. Next, the importance of meta-paths of the L&I visualization network was calculated. Finally, a complex big data L&I visualization network was established, and the associations between information nodes were analyzed in detail. Experimental results verify the effectiveness of the proposed algorithm.

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Geospatial Data Analysis: A Review of Theory and Methods

10.34048/2017.3.f2 ◽

2017 ◽

Author(s):

Prof. Rajagopalan S ◽

Yogalakshmi Jayabal

Keyword(s):

Big Data ◽

Data Analysis ◽

Data Collection ◽

Geospatial Data ◽

Data Generation ◽

Vast Amount ◽

Temporal Aspect ◽

Geospatial Data Collection

A vast amount of data is generated and collected every moment and often, data has a spatial and/or temporal aspect. This increasing data generation and collection is resulting in increasing volume and varying formats of data being collected and the geospatial data collection is no exception. This posses challenges in storing, processing, analyzing and visualizing the geospatial data. This paper discusses the big data paradigm of the geospatial data and presents a taxonomy for analysis of the geospatial data. The existing literature is studied and discussed based on the proposed taxonomy for analysis of geospatial data.

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Geomarketing Big Data Analysis

INFORMACIONNYE TEHNOLOGII ◽

10.17587/it.27.180-187 ◽

2021 ◽

Vol 27 (4) ◽

pp. 180-187

Author(s):

S. V. Shaytura ◽

◽

D. A. Galkin ◽

Keyword(s):

Big Data ◽

Data Analysis ◽

Data Clustering ◽

Big Data Analysis ◽

Geospatial Data ◽

Shopping Center ◽

Housing Cost ◽

Cost Assessment ◽

Bank Branch ◽

New Approaches

The accumulation of a large amount of geospatial data requires new approaches to their processing and visualization. One of these approaches is the creation of a geomarketing system with a fundamentally new toolkit based on data clustering. The capabilities of such a system are shown using examples of housing cost assessment, determining the location of a new shopping center, a bank branch and a clinic.

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Intelligent Data Analysis and its challenges in big data environment

2014 IEEE International Conference on System Science and Engineering (ICSSE) ◽

10.1109/icsse.2014.6887915 ◽

2014 ◽

Cited By ~ 2

Author(s):

Weichang Kong ◽

Qidi Wu ◽

Li Li ◽

Fei Qiao

Keyword(s):

Big Data ◽

Data Analysis ◽

Intelligent Data Analysis ◽

Data Environment

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Layered software patterns for data analysis in big data environment

International Journal of Automation and Computing ◽

10.1007/s11633-016-1043-x ◽

2017 ◽

Vol 14 (6) ◽

pp. 650-660

Author(s):

Hossam Hakeem

Keyword(s):

Big Data ◽

Data Analysis ◽

Software Patterns ◽

Data Environment

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Information Visualization from the Perspective of Big Data Analysis and Fusion

WSEAS TRANSACTIONS ON COMPUTERS ◽

10.37394/23205.2021.20.37 ◽

2021 ◽

Vol 20 ◽

pp. 352-361

Author(s):

Xiang Lin

Keyword(s):

Big Data ◽

Data Analysis ◽

Information Visualization ◽

Information Fusion ◽

Big Data Analysis ◽

Data Sources ◽

Visualization Technique ◽

Network Layout ◽

Data Volume ◽

Data Environment

In the big data environment, the visualization technique has been increasingly adopted to mine the data on library and information (L&I), with the diversification of data sources and the growth of data volume. However, there are several defects with the research on information association of L&I visualization network: the lack of optimization of network layout algorithms, and the absence of L&I information fusion and comparison in multiple disciplines, in the big data environment. To overcome these defects, this paper explores the visualization of L&I from the perspective of big data analysis and fusion. Firstly, the authors analyzed the topology of the L&I visualization network, and calculated the metrics for the construction of L&I visualization topology map. Next, the importance of meta-paths of the L&I visualization network was calculated. Finally, a complex big data L&I visualization network was established, and the associations between information nodes were analyzed in details. Experimental results verify the effectiveness of the proposed algorithm

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