Acquisition of Data for Plasma Simulation by Automated Extraction of Terminology from Article Abstracts
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概要
- 論文の詳細を見る
Computer simulation of burning plasmas as well as computational plasma modeling in image processing requires a number of accurate data, in addition to a relevant model framework. To this aim, it is very important to recognize, obtain and evaluate data relevant for such a simulation from the literature. This work focuses on the simultaneous search of relevant data across various online databases, extraction of cataloguing and numerical information, and automatic recognition of specific terminology in the text retrieved. The concept is illustrated on the particular terminology of Atomic and Molecular data relevant to edge plasma simulation. The IAEA search engine GENIE and the NIFS search engine Joint Search 2 are compared and discussed. Accurate modeling of the imaged object is considered to be the ultimate challenge in improving the resolution limits of plasma imaging.
- 社団法人 プラズマ・核融合学会の論文
著者
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Murata Masaki
National Inst. Information And Communications Technol.
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Sasaki Akira
Kansai Research Establishment Japan Atomic Energy Research Institute
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SUZUKI Manabu
School of Systems Science, Arkansas Technical University, 1811 N. Boulder Ave., Corley 201-C, AR 72801-2222, USA
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RHEE Yongjoo
Korea Atomic Energy Research Institute, P.O. Box 105, Yuseong, Daejeon 305-600, Korea
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KATO Daiji
Coordination Research Center, National Institute for Fusion Science, Oroshi-cho, Toki, Gifu 509-5292, Japan
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PICHL Lukáš
Division of Natural Sciences, International Christian University, Osawa 3-10-2, Mitaka, Tokyo 181-8585 Japan
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MURAKAMI Izumi
Coordination Research Center, National Institute for Fusion Science, Oroshi-cho, Toki, Gifu 509-5292, Japan
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SASAKI Akira
Kansai Photon Science Institute, Japan Atomic Energy Agency, 8-1 Umemidai, Kizu-cho, Kyoto 619-0215, Japan
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- Acquisition of Data for Plasma Simulation by Automated Extraction of Terminology from Article Abstracts
- Automatic F-term Classification of Japanese Patent Documents Using the k-Nearest Neighborhood Method and the SMART Weighting
- Use of Multiple Documents as Evidence with Decreased Adding in a Japanese Question-answering System