Adaptive information extraction of disaster information from Twitter

College

College of Computer Studies

Department/Unit

Software Technology

Document Type

Conference Proceeding

Source Title

Proceedings - ICACSIS 2014: 2014 International Conference on Advanced Computer Science and Information Systems

First Page

286

Last Page

289

Publication Date

3-23-2014

Abstract

With the popularity of the Internet and social media platforms, information that is potentially useful in disaster response becomes available online in the hours and days immediately following a disaster. The use of information extraction in retrieving relevant disaster information from all these crowdsourced data would provide more information coming from both official reports, and the affected people themselves which in turn facilitate better decision making environments for disaster managers. This paper describes a system which performs an adaptive information retrieval of disaster related information coming from Twitter. Result shows 94.33% accuracy when extracting disaster and location information in the typhoon corpus while 90.79% accuracy for the fire corpus. © 2014 IEEE.

html

Digitial Object Identifier (DOI)

10.1109/ICACSIS.2014.7065859

Disciplines

Computer Sciences

Keywords

Information retrieval; Information storage and retrieval systems—Disaster relief; Twitter; Microblogs; Emergency management

Upload File

wf_no

This document is currently not available here.

Share

COinS