Paper Info
Title
Semantic Enrichment of Movement Behavior with Foursquare - A Visual Analytics Approach
Abstract
In recent years many approaches have been developed that efficiently and effectively visualize movement data, e.g. by providing suitable aggregation strategies to reduce visual clutter. Analysts can use them to identify distinct movement patterns, such as trajectories with similar direction, form, length, and speed. However, less effort has been spent on finding the semantics behind movements, i.e. why somebody or something is moving. This can be of great value for different applications, such as product usage and consumer analysis, to better understand urban dynamics, and to improve situational awareness. Unfortunately, semantic information often gets lost when data is recorded. Thus, we suggest to enrich trajectory data with POI information using social media services and show how semantic insights can be gained. Furthermore, we show how to handle semantic uncertainties in time and space, which result from noisy, unprecise, and missing data, by introducing a POI decision model in combination with highly interactive visualizations. Finally, we evaluate our approach with two case studies on a large electric scooter dataset and test our model on data with known ground truth.
Year
DOI
Venue
2015
10.1109/TVCG.2014.2371856
Visualization and Computer Graphics, IEEE Transactions  
Keywords
Field
DocType
foursquare,geographic visualization,semantic movement analysis,social media,visual analytics,semantics,trajectory,data visualization,uncertainty,visualization,data models
Geovisualization,Data modeling,Computer vision,Data visualization,Situation awareness,Visualization,Computer science,Visual analytics,Artificial intelligence,Missing data,Semantics
Journal
Volume
Issue
ISSN
PP
99
1077-2626
Citations 
PageRank 
References 
11
0.43
27
Authors
3
Name
Order
Citations
PageRank
Robert Krüger1763.68
Dennis Thom217810.72
Thomas Ertl34417401.52