| Project/Area Number |
11480082
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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 |
Intelligent informatics
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| Research Institution | International Research Center for Japanese Studies |
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Principal Investigator |
YAMADA Shoji International Research Center for Japanese Studies, Research Department, Associate Professor, 研究部, 助教授 (20248751)
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| Co-Investigator(Kenkyū-buntansha) |
KASAYA Kazuhiko International Research Center for Japanese Studies,Research Department,Professor, 研究部, 教授 (90124198)
KAWAGUCHI Hiroshi Tezukayama University Faculuty of Business Administration Associate Professor, 経営情報学部, 助教授 (80224749)
SHIBAYAMA Mamoru Osaka City university,Media Center,Professor, 学術情報総合センター, 教授 (10162645)
KATO Nei Tohoku University,Graduate School of Information Science Associate Professor, 大学院・情報科学研究科, 助教授 (00236168)
KOJIMA Masami Tohoku Institute of Technology Faculty of Engineering,Associate Professor, 工学部, 助教授 (60085420)
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| Project Period (FY) |
1999 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥10,500,000 (Direct Cost: ¥10,500,000)
Fiscal Year 2001: ¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 2000: ¥5,400,000 (Direct Cost: ¥5,400,000)
Fiscal Year 1999: ¥3,000,000 (Direct Cost: ¥3,000,000)
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| Keywords | Historical Document / Character Recognition / OCR / Character Segmantation / Electrical Dictionary / 知識ベース / 用例データベース / 文字データベース / 用例デ-タベース |
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| Research Abstract |
In this research project, we studied the following four research topics : (1) Structuring the knowledge of Historical Document Understanding, (2) Study of the Historical Chara cter Recognition using our Historical Character OCR dictionary, (3) Developing a Dictionary for Historical Character Recognition, and (4) Developing a proto-type system of a computer ized Historical Character Dictionary (1) We developed a Historical Corpus Database analyzing many loan contracts consists of 1, 300 documents and 243, 000 characters. The common and frequent expressions are extracted from the documents. By using the data, we developed a proto-type of Historical Document Analysis Supporting System using n-gram method. Through an usability test, efficiency of the interface is confirmed statistically. (2) We developed some Historical Character Recognition methods using neural network. (3) Besides the database described in (1), we made another Historical Character Database of "Kuzushi-ji Kaidoku Jiten" published from Tokyoudo Syoten, which is one of the standard dictionary. The dictionary includes 25, 000 characters. (4) We have done some basic studies and have made a proto-type system of portable electrical dictionary, which could be searched by pronunciation, shape, and stroke order.
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