A Study on Digital Library System for Experimental Information Extraction, Visualization and Recommendation
| Project/Area Number |
15H02789
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Library and information science/Humanistic social informatics
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| Research Institution | National Institute of Informatics |
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Principal Investigator |
Takasu Atsuhiro 国立情報学研究所, コンテンツ科学研究系, 教授 (90216648)
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| Co-Investigator(Kenkyū-buntansha) |
正田 備也 長崎大学, 工学研究科, 准教授 (60413928)
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| Research Collaborator |
Ohta Manabu
Maneeroj Saranya
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2018)
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| Budget Amount *help |
¥15,860,000 (Direct Cost: ¥12,200,000、Indirect Cost: ¥3,660,000)
Fiscal Year 2017: ¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2016: ¥5,330,000 (Direct Cost: ¥4,100,000、Indirect Cost: ¥1,230,000)
Fiscal Year 2015: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
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| Keywords | 電子図書館 / 情報抽出 / 情報推薦 / 潜在確率モデル / トピックモデル |
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| Outline of Final Research Achievements |
Researchers need to survey research trend in the related research fields in various tasks, such as research planning, research trend analysis, and writing papers. Digital libraries have been playing an important role in providing research papers fulltext. Fulltext search is a main technology for retrieving research papers. This study focuses on experiment information included in papers and developed sequence analysis models for extracting experiment information. We also developed a recommender system for actively providing scholarly information.
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| Academic Significance and Societal Importance of the Research Achievements |
学術論文に含まれる実験情報は、研究成果を定量的に提示するとともに、科学的発見の根拠を示す情報として重要である。本研究の実験情報の抽出・提示技術は、研究者の研究動向の調査および分析の効率化に大きく寄与することが期待される。また、本研究の成果である利用者のニーズにあわせて情報を能動的に提供する情報推薦法は、学術情報のみならず、多種多様な情報推薦に利用可能な汎用性を備えた技術となっている。
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Report
(4 results)
Research Products
(27 results)
