Geographic context-aware text mining: enhance social media message classification for situational awareness by integrating spatial and temporal features
Author:
Affiliation:
1. Spatial Computing and Data Mining Lab, Department of Geography, University of Wisconsin-Madison, Madison, WI, USA
2. Department of Geography, Pennsylvania State University, University Park, PA, USA
Funder
University of Wisconsin-Madison
National Science Foundation
Publisher
Informa UK Limited
Subject
General Earth and Planetary Sciences,Computer Science Applications,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/17538947.2021.1968048
Reference63 articles.
1. Twitter for crisis communication: lessons learned from Japan's tsunami disaster
2. Evaluation of Weather Radar with Pulse Compression: Performance of a Fuzzy Logic Tornado Detection Algorithm
3. Ansari, Steve, S. Del Greco, and B. Hankins. 2010. “The Weather and Climate Toolkit.” Paper Presented at the AGU Fall Meeting Abstracts, San Francisco, CA, December 13–17.
4. Ashktorab, Zahra, Christopher Brown, Manojit Nandi, and Aron Culotta. 2014. “Tweedr: Mining Twitter to Inform Disaster Response.” Paper Presented at the 11th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2014), University Park, PA.
5. Geo-located community detection in Twitter with enhanced fast-greedy optimization of modularity: the case study of typhoon Haiyan
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Location Reference Recognition from Texts: A Survey and Comparison;ACM Computing Surveys;2023-11-27
2. Geo-knowledge-guided GPT models improve the extraction of location descriptions from disaster-related social media messages;International Journal of Geographical Information Science;2023-10-09
3. The State of the Art in Deep Learning Applications, Challenges, and Future Prospects: A Comprehensive Review of Flood Forecasting and Management;Sustainability;2023-07-04
4. Applicability Analysis and Ensemble Application of BERT with TF-IDF, TextRank, MMR, and LDA for Topic Classification Based on Flood-Related VGI;ISPRS International Journal of Geo-Information;2023-06-09
5. A Deep Learning Model of Spatial Distance and Named Entity Recognition (SD-NER) for Flood Mark Text Classification;Water;2023-03-20
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3