Journal of Disaster Research
Online ISSN : 1883-8030
Print ISSN : 1881-2473
ISSN-L : 1881-2473
Special Issue on Disaster and Big Data Part 2
Text-Data Reduction Method to Grasp the Sequence of a Disaster Situation: Case Study of Web News Analysis of the 2015 Typhoons 17 and 18
Shosuke SatoToru OkamotoShunichi Koshimura
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JOURNAL OPEN ACCESS

2017 Volume 12 Issue 2 Pages 329-334

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Abstract

This study aims to compress web news, delivered as a big-data source after disasters. In this paper, article clustering, which is a combination of conventional means and an algorithm that selects the representative articles of each cluster, is designed and adopted. Experiments are conducted by evaluators. The proposed algorithm is in accord with the evaluators for 50% of the clustering and for about 30% to 40% of the representative-article selection.

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