2022 Fiscal Year Final Research Report
Mapping emerging research trends from dynamic networks via sparse representation
Project/Area Number |
17K12794
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Library and information science/Humanistic social informatics
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Research Institution | Doshisha University |
Principal Investigator |
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Project Period (FY) |
2017-04-01 – 2023-03-31
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Keywords | 学術データ分析 / サイエンスマッピング / トレンド分析 / トレンド可視化 |
Outline of Final Research Achievements |
The objective of this research project was to establish a research trend mapping technique that enables simultaneous exploration of the latest topics and visualization of their evolution from academic big data. During the research period, we proposed a sparse optimization method that preserves only the rapidly changing parts in the time-series of co-word networks. The obtained results were published in Scientometrics, and the source code was made publicly available on the researcher's website. Furthermore, the application results were presented as a demo paper at JCDL 2021.
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Free Research Field |
マルチメディア情報検索
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Academic Significance and Societal Importance of the Research Achievements |
過去の状態に比べて急激に変化したノードとエッジを可視化するという目的におけるスパース表現の採用は本研究の独創的な点であり学術的な意義が大きい。 各研究分野で急成長している技術やその発展の様子を解明することは、研究関係者や政策立案者の俯瞰的視野の養成につながる。本研究で構築した手法をウェブ上で公開することで、関連分野の技術開発促進に貢献した。
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