| Project/Area Number |
15K16090
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Web informatics, Service informatics
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| Research Institution | Keio University |
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Principal Investigator |
Morita Takeshi 慶應義塾大学, 理工学部(矢上), 准教授(有期) (50590171)
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| Project Period (FY) |
2015-04-01 – 2019-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2017: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2016: ¥650,000 (Direct Cost: ¥500,000、Indirect Cost: ¥150,000)
Fiscal Year 2015: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
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| Keywords | オントロジー / セマンティックWeb / オントロジー学習 / Linked Data / クラススキーマ / Wikipedia / オントロジーアライメント / WordNet |
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| Outline of Final Research Achievements |
In recent years, technology for publishing and sharing software-readable data on the web called Linked Open Data (LOD) has attracted attention. With the widespread use of LODs, the web will become a huge knowledge base, enabling data integration and reuse across applications. Although DBpedia and YAGO are famous as hubs for integrating LOD, there is an issue that the definition of the ontology that defines the structure of LOD is insufficient. In this research, we proposed a method to construct large-scale ontology from the text information of English Wikipedia. From the evaluation, we demonstrated that the ontology could complement DBpedia and YAGO.
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| Academic Significance and Societal Importance of the Research Achievements |
本研究で構築した大規模オントロジーは，ナレッジグラフを活用した質問応答システム，ドメインオントロジーを構築するための参照リソース，ナレッジグラフの推論を用いた意味検索，アプリケーションを横断したデータ統合・再利用等への活用が期待でき，実用性の高いものである．また，評価結果より，本研究で構築した大規模オントロジーは，現在，LODのハブとして活用されているDBpediaやYAGOを補完できる可能性があり，今後，DBpediaやYAGOを活用したアプリケーションへの適用も期待できる．
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