86 citations · 164 across the 9 of their papers we have counts for
7 papers · 1 filter
Ovid: A Machine Learning Approach for Automated Vandalism Detection in OpenStreetMap
Nicolas Tempelmeier, Elena Demidova
OpenStreetMap is a unique source of openly available worldwide map data, increasingly adopted in real-world applications. Vandalism detection in OpenStreetMap is critical and remar…
Attention-Based Vandalism Detection in OpenStreetMap
Nicolas Tempelmeier, Elena Demidova
OpenStreetMap (OSM), a collaborative, crowdsourced Web map, is a unique source of openly available worldwide map data, increasingly adopted in Web applications. Vandalism detection…
GeoVectors: A Linked Open Corpus of OpenStreetMap Embeddings on World Scale
Nicolas Tempelmeier, Simon Gottschalk, Elena Demidova
OpenStreetMap (OSM) is currently the richest publicly available information source on geographic entities (e.g., buildings and roads) worldwide. However, using OSM entities in mach…
Deep Information Fusion for Electric Vehicle Charging Station Occupancy Forecasting
Ashutosh Sao, Nicolas Tempelmeier, Elena Demidova
With an increasing number of electric vehicles, the accurate forecasting of charging station occupation is crucial to enable reliable vehicle charging. This paper introduces a nove…
Towards Neural Schema Alignment for OpenStreetMap and Knowledge Graphs
Alishiba Dsouza, Nicolas Tempelmeier, Elena Demidova
OpenStreetMap (OSM) is one of the richest openly available sources of volunteered geographic information. Although OSM includes various geographical entities, their descriptions ar…
Mining Topological Dependencies of Recurrent Congestion in Road Networks
Nicolas Tempelmeier, Udo Feuerhake, Oskar Wage +1
The discovery of spatio-temporal dependencies within urban road networks that cause Recurrent Congestion (RC) patterns is crucial for numerous real-world applications, including ur…