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

    ASJC Scopus subject areas

    • Safety, Risk, Reliability and Quality
    • Engineering (miscellaneous)

    Fingerprint

    Dive into the research topics of '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'. Together they form a unique fingerprint.

    Cite this