Visualizing High-Risk Paths using Geo-tagged Social Data for Disaster Mitigation-Reference-Cited by-同舟云学术

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Visualizing High-Risk Paths using Geo-tagged Social Data for Disaster Mitigation

Published:2016-10-31 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 9th ACM SIGSPATIAL Workshop on Location-based Social Networks
language:
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Author:

Kanno Masaki¹,Ehara Yo²,Hirota Masaharu³,Yokoyama Shohei⁴,Ishikawa Hiroshi¹

Affiliation:

1. Tokyo Metropolitan University, Hino-shi, Tokyo, Japan

2. National Institute of Advanced Industrial Science and Technology, AIST Tokyo Waterfront BIO-IT, Aomi, Koto-ku, Japan

3. Department of Information Engineering, National Institute of Technology, Oita College, Oita-shi, Oita, Japan

4. Shizuoka University, Naka-ku, Hamamatsu-shi, Shizuoka, Japan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3021304.3021308

Reference17 articles.

1. P. Crucitti V. Latora and S. Porta. Centrality in networks of urban streets. Chaos: an interdisciplinary journal of nonlinear science 16(1):015113 2006. P. Crucitti V. Latora and S. Porta. Centrality in networks of urban streets. Chaos: an interdisciplinary journal of nonlinear science 16(1):015113 2006.

2. "OMG, from here, I can see the flames!"

3. An Analysis of Twitter Messages in the 2011 Tohoku Earthquake

4. Centrality in social networks conceptual clarification

5. Proposing Centrality Measures Considering Actual Distances and Applications to Extracting Important Sightseeing Spots

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