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Extracting a Keyword Network of Flood Disaster Measures

Extracting a Keyword Network of Flood Disaster Measures. Motoki Miura, Mitsuhiro Tokuda , and Daiki Kuwahara Department of Civil and Architectural Engineering, Faculty of Engineering, Kyushu Institute of Technology. Risk of Flooding.

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Extracting a Keyword Network of Flood Disaster Measures

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  1. Extracting a Keyword Network ofFlood Disaster Measures Motoki Miura, Mitsuhiro Tokuda, and DaikiKuwahara Department of Civil and Architectural Engineering, Faculty of Engineering, Kyushu Institute of Technology

  2. Risk of Flooding • Frequent Extra-tropical cyclones by greenhouse effect increase the risk of flood disaster and localized heavy rainsin the decade • To prevent/reduce the flooding damage, anti-disaster headquarters must have overall knowledge of anti-disaster measures(ex. know-hows, tips)

  3. Purpose • To provide overall knowledge of anti-disaster measures, • (1) we analyze measures from previous disaster, and • (2) we visualize the structure of measures as “summary” • The “summary” can be effective to improve quality of disaster-recovery services/cares

  4. Sample of the anti-disaster measures for city-center headquarter (1/2) • Do not hesitate to counsel refugees.Safety of human life is most important. • We observed that even in emergency, people do not evacuate. To make people aware of the need for evacuation is crucial. • Volunteer center should be established immediately. Volunteer is not only a worker, but is also hope for recovery.

  5. Sample of the anti-disaster measures for city-center headquarter (2/2) • A huge amount of garbage is thrown away. A temporary garbage dump should be constructed immediately. For quick processing, separation of garbage should be promoted. • Do not hesitate to act for relief even if it costs much money. Any financial issue can be settled afterwards. The head of municipality must prove that we can afford the refugee costs.

  6. Preprocess • 828 measures are taken from Book “Know-hows of prevention, reduction and recovering of flood disaster --- message from the striken areas” • We manually labeled a few keywords to each measure (source text) , to represent the original context/meaning

  7. The Labeling Sample (1/2) • Do not hesitate to counsel refugees.Safety of human life is most important. • Life | Refuge | Refugees Counsel • We observed that even in emergency, people do not evacuate. To make people aware of the need for evacuation is crucial. • Refuge | Refugees Counsel | Publication | Tense Situation • Volunteer center should be established immediately. Volunteer is not only a worker, but is also hope for recovery. • Volunteer Center | Volunteer | Victims | Encouragement

  8. The Labeling Sample (2/2) • A huge amount of garbage is thrown away. A temporary garbage dump should be constructed immediately. For quick processing, separation of garbage should be promoted. • Garbage | Temporal Place | Garbage Separation • Do not hesitate to act for relief even if it costs much money. Any financial issue can be settled afterwards. The head of municipality must prove that we can afford the refugee costs. • Budget | Immediately After | Head of Municipality

  9. Visualizing System (based on Prefuse toolkit)

  10. Visualize Graph (Node: Measure + KW) • 828 measures, 188 keywords, 2.539 links

  11. Visualize Graph (Node: KW only) • Eliminate Measure-ID nodes, and link neighboring keywords directly • 188 keyword nodes, 3.450 links (911 links are added) 3.450 links

  12. Visualize Graph (KW only, link reduced) • Only the most frequent keyword on the measure can link to another • 188 keyword nodes, 1.961 links (43% of links reduced, but still dense) 3.450 links 1.961 links

  13. Co-occurrence Keyword Network • Consider co-occurrence degree (numbers of overlapping links) among keyword nodes Disposal Disposal 419 Degree = 3 Electric Appliance 428 417 Electric Appliance Degree = 1 Making Resource Making Resource

  14. Frequency of co-occurrence degree

  15. 6-24 co-occurrence graph • 6 co-occurrence : green 32 links over 6 co-occurrence: red 34 links

  16. Conclusion and Future Work • We discussed our trials to analyze know-hows (measures) on flood disaster measures • We found the co-occurrence keyword network can represent meaningful relationships • The graph can provide overview for anti-disaster headquarters and citizens • Future Work • Semi-Automatic labeling • Improve interface design for quick graph analysis

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