Abstract
This research aims to develop a framework for smoothly obtaining disaster information from multiple web services through a knowledge base of disaster information. In Japan, where natural disasters occur frequently, there is a need for a system that can utilize disaster information transmitted on the Web from various locations in disaster-stricken areas for rescue operations and disaster recovery when a disaster occurs. Since such information is posted to many web services, searchers must refer to multiple web services to obtain the desired information. In this study, we propose understanding the characteristics of disaster information posted on each web service and using them as a guide for searchers to obtain disaster information smoothly. To achieve this goal, we tried to construct a vocabulary set of disaster information by acquiring textual information from two different data sources and using word embedding and clustering.
Information
Book title
Proc. The 2024 Conference on Technologies and Applications of Artificial Intelligence
Date of issue
2024/12/06
Date of presentation
2024/12/06
Location
Hsinchu city, Taiwan (National Tsing Hua University)
Citation
Megumi Yasuo, Hiroyuki Fujishiro, Mitsunori Matsushita. Effects of online news comments on Attitude Formation of Readers, Proc. The 2024 Conference on Technologies and Applications of Artificial Intelligence, 2024.