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A Framework for Using Self-Organizing Maps to Analyze Spatio-Temporal Patterns, Exemplified by Analysis of Mobile Phone Usage

Andrienko, Gennady and Andrienko, Natalia and Bak, Peter and Bremm, Sebastian and Keim, Daniel A. and Landesberger, Tatiana von and Pölitz, Christian and Schreck, Tobias (2010):
A Framework for Using Self-Organizing Maps to Analyze Spatio-Temporal Patterns, Exemplified by Analysis of Mobile Phone Usage.
In: Journal of Location Based Services, pp. 200-221, 4, (3-4), DOI: 10.1080/17489725.2010.532816, [Article]

Abstract

We suggest a visual analytics framework for the exploration and analysis of spatially and temporally referenced values of numeric attributes. The framework supports two complementary perspectives on spatio-temporal data: as a temporal sequence of spatial distributions of attribute values (called spatial situations) and as a set of spatially referenced time series of attribute values representing local temporal variations. To handle a large amount of data, we use the self-organising map (SOM) method, which groups objects and arranges them according to similarity of relevant data features. We apply the SOM approach to spatial situations and to local temporal variations and obtain two types of SOM outcomes, called space-in-time SOM and time-in-space SOM, respectively. The examination and interpretation of both types of SOM outcomes are supported by appropriate visualisation and interaction techniques. This article describes the use of the framework by an example scenario of data analysis. We also discuss how the framework can be extended from supporting explorative analysis to building predictive models of the spatio-temporal variation of attribute values. We apply our approach to phone call data showing its usefulness in real-world analytic scenarios.

Item Type: Article
Erschienen: 2010
Creators: Andrienko, Gennady and Andrienko, Natalia and Bak, Peter and Bremm, Sebastian and Keim, Daniel A. and Landesberger, Tatiana von and Pölitz, Christian and Schreck, Tobias
Title: A Framework for Using Self-Organizing Maps to Analyze Spatio-Temporal Patterns, Exemplified by Analysis of Mobile Phone Usage
Language: English
Abstract:

We suggest a visual analytics framework for the exploration and analysis of spatially and temporally referenced values of numeric attributes. The framework supports two complementary perspectives on spatio-temporal data: as a temporal sequence of spatial distributions of attribute values (called spatial situations) and as a set of spatially referenced time series of attribute values representing local temporal variations. To handle a large amount of data, we use the self-organising map (SOM) method, which groups objects and arranges them according to similarity of relevant data features. We apply the SOM approach to spatial situations and to local temporal variations and obtain two types of SOM outcomes, called space-in-time SOM and time-in-space SOM, respectively. The examination and interpretation of both types of SOM outcomes are supported by appropriate visualisation and interaction techniques. This article describes the use of the framework by an example scenario of data analysis. We also discuss how the framework can be extended from supporting explorative analysis to building predictive models of the spatio-temporal variation of attribute values. We apply our approach to phone call data showing its usefulness in real-world analytic scenarios.

Journal or Publication Title: Journal of Location Based Services
Volume: 4
Number: 3-4
Uncontrolled Keywords: Forschungsgruppe Visual Search and Analysis (VISA), Spatio-temporal data, Geodata visualization, Self-organizing maps (SOM), Cluster analysis, Visual analysis, Geovisualization
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1080/17489725.2010.532816
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