Journal of the Japanese Society for Artificial Intelligence
Online ISSN : 2435-8614
Print ISSN : 2188-2266
Print ISSN:0912-8085 until 2013
Aiding Discovery of Risky Faults by Indexing Earthquake History with KeyGraph(Discovery Science)
Yukio OHSAWAMasahiko YACHIDA
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2000 Volume 15 Issue 4 Pages 665-672

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Abstract

KeyGraph, an automatic document indexing method for extracting keywords expressing the assertions of a document, i. e. assertions supported by the outlines based on the basic concepts of the document, is applied to detecting risky active faults from earthquake history data. Here a history data is regarded as a document to be indexed, and active faults stressed strongly i. e. with near-future earthquake risks are obtained as keywords asserted in the document. This paper presents this method and its seismologic semantics. The semantics shows that KeyGraph is a model of earthquake occurrences, which considers less details of local land crust activities than in seismology, but more of global interactions among active faults. Experimentally, faults with near-future earthquake risks were obtained with high accuracies, and the shifts of risky areas after big earthquakes datected by KeyGraph corresponded with realistic tectonics.

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© 2000 The Japaense Society for Artificial Intelligence
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