%0 Conference Paper %1 krueger2014visual %A Krueger, R. %A Thom, D. %A Ertl, T. %B 2014 IEEE Pacific Visualization Symposium %D 2014 %K diss inthesis visualization %P 193-200 %R 10.1109/PacificVis.2014.57 %T Visual Analysis of Movement Behavior Using Web Data for Context Enrichment %U http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6787167 %X With increasing use of GPS devices more and more location-based information is accessible. Thus not only more movements of people are tracked but also POI (point of interest) information becomes available in increasing geo-spatial density. To enable analysis of movement behavior, we present an approach to enrich trajectory data with semantic POI information and show how additional insights can be gained. Using a density-based clustering technique we extract 1.215 frequent destinations of ~150.000 user movements from a large e-mobility database. We query available context information from Foursquare, a popular location-based social network, to enrich the destinations with semantic background. As GPS measurements can be noisy, often more then one possible destination is found and movement patterns vary over time. Therefore we present highly interactive visualizations that enable an analyst to cope with the inherent geospatial and behavioral uncertainties.

@inproceedings{krueger2014visual, abstract = {With increasing use of GPS devices more and more location-based information is accessible. Thus not only more movements of people are tracked but also POI (point of interest) information becomes available in increasing geo-spatial density. To enable analysis of movement behavior, we present an approach to enrich trajectory data with semantic POI information and show how additional insights can be gained. Using a density-based clustering technique we extract 1.215 frequent destinations of ~150.000 user movements from a large e-mobility database. We query available context information from Foursquare, a popular location-based social network, to enrich the destinations with semantic background. As GPS measurements can be noisy, often more then one possible destination is found and movement patterns vary over time. Therefore we present highly interactive visualizations that enable an analyst to cope with the inherent geospatial and behavioral uncertainties.}, added-at = {2017-01-10T09:40:31.000+0100}, author = {Krueger, R. and Thom, D. and Ertl, T.}, biburl = {https://www.bibsonomy.org/bibtex/22f737a3b344dc376a464c493fe4e4758/becker}, booktitle = {2014 IEEE Pacific Visualization Symposium}, doi = {10.1109/PacificVis.2014.57}, interhash = {6e402f455986ae8817adf9d6733669de}, intrahash = {2f737a3b344dc376a464c493fe4e4758}, issn = {2165-8765}, keywords = {diss inthesis visualization}, month = {March}, pages = {193-200}, timestamp = {2017-01-10T09:40:50.000+0100}, title = {Visual Analysis of Movement Behavior Using Web Data for Context Enrichment}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6787167}, year = 2014 }