Data-Driven Exploration of Real-Time Geospatial Text Streams
Abstract
Geolocated social media data streams are challenging data sources due to volume, velocity, variety, and unorthodox vocabulary. However, they also are an unrivaled source of eye-witness accounts to establish remote situational awareness. In this paper we summarize some of our approaches to separate relevant information from irrelevant chatter using unsupervised and supervised methods alike. This allows the structuring of requested information as well as the incorporation of unexpected events into a common overview of the situation. A special focus is put on the interplay of algorithms, visualization, and interaction.
Cite
Text
Bosch et al. "Data-Driven Exploration of Real-Time Geospatial Text Streams." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015. doi:10.1007/978-3-319-23461-8_14Markdown
[Bosch et al. "Data-Driven Exploration of Real-Time Geospatial Text Streams." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015.](https://mlanthology.org/ecmlpkdd/2015/bosch2015ecmlpkdd-datadriven/) doi:10.1007/978-3-319-23461-8_14BibTeX
@inproceedings{bosch2015ecmlpkdd-datadriven,
title = {{Data-Driven Exploration of Real-Time Geospatial Text Streams}},
author = {Bosch, Harald and Krüger, Robert and Thom, Dennis},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2015},
pages = {203-207},
doi = {10.1007/978-3-319-23461-8_14},
url = {https://mlanthology.org/ecmlpkdd/2015/bosch2015ecmlpkdd-datadriven/}
}