書誌事項
- タイトル別名
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- Aiding Discovery of Risky Faults by Indexing Earthquake History with KeyGraph(Discovery Science)
- キーワード抽出法KeyGraphの転用による地震履歴データからの要注意活断層発見支援
- キーワード チュウシュツホウ KeyGraph ノ テンヨウ ニ ヨル ジシン リレキ データ カラ ノ ヨウ チュウイカツダンソウ ハッケン シエン
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説明
<p>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.</p>
収録刊行物
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- 人工知能
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人工知能 15 (4), 665-672, 2000-07-01
一般社団法人 人工知能学会
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詳細情報 詳細情報について
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- CRID
- 1390004222625973248
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- NII論文ID
- 110002808299
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- NII書誌ID
- AN10067140
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- ISSN
- 09128085
- 24358614
- 21882266
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- NDL書誌ID
- 5439821
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可