Finding Incident-Related Social Media Messages for Emergency Awareness
Abstract
An information retrieval framework is proposed which searches for incident-related social media messages in an automated fashion. Using P2000 messages as an input for this framework and by extracting location information from text, using simple natural language processing techniques, a search for incident-related messages is conducted. A machine learned ranker is trained to create an ordering of the retrieved messages, based on their relevance. This provides an easy accessible interface for emergency response managers to aid them in their decision making process.
Cite
Text
Nieuwenhuijse et al. "Finding Incident-Related Social Media Messages for Emergency Awareness." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016. doi:10.1007/978-3-319-46131-1_15Markdown
[Nieuwenhuijse et al. "Finding Incident-Related Social Media Messages for Emergency Awareness." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2016.](https://mlanthology.org/ecmlpkdd/2016/nieuwenhuijse2016ecmlpkdd-finding/) doi:10.1007/978-3-319-46131-1_15BibTeX
@inproceedings{nieuwenhuijse2016ecmlpkdd-finding,
title = {{Finding Incident-Related Social Media Messages for Emergency Awareness}},
author = {Nieuwenhuijse, Alexander and Bakker, Jorn and Pechenizkiy, Mykola},
booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
year = {2016},
pages = {67-70},
doi = {10.1007/978-3-319-46131-1_15},
url = {https://mlanthology.org/ecmlpkdd/2016/nieuwenhuijse2016ecmlpkdd-finding/}
}