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

Research output: Contribution to journalArticlepeer-review

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 50s% of the clustering and for about 30s% to 40s% of the representative-article selection.

Original languageEnglish
Pages (from-to)329-334
Number of pages6
JournalJournal of Disaster Research
Volume12
Issue number2
DOIs
Publication statusPublished - 2017 Mar

Keywords

  • Common operational picture (COP)
  • Disaster information system
  • Disaster situation
  • Text data
  • Web news

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