Study on Information Retrieval based on Similarity Calculation of Intra-Document Structure
| Project/Area Number |
11680383
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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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 | Yokohama National University |
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Principal Investigator |
MORI Tatsunori Yokohama National University, Faculty of Engineering, Associate, 工学部, 助教授 (70212264)
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| Co-Investigator(Kenkyū-buntansha) |
NAKAGAWA Hiroshi University of Tokyo, Information Technology Center, Professor, 情報基盤センター, 教授 (20134893)
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| Project Period (FY) |
1999 – 2000
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| Project Status |
Completed (Fiscal Year 2000)
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| Budget Amount *help |
¥3,600,000 (Direct Cost: ¥3,600,000)
Fiscal Year 2000: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 1999: ¥2,500,000 (Direct Cost: ¥2,500,000)
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| Keywords | Retrieval of similar documents / Extraction of Numerical Expressions / Extraction of Named Entity / Question Answering / Information Retrieval / Information Extraction |
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| Research Abstract |
The purpose of this research is establishment of the method for "content"-based information retrieval. In our research, the "content" is regarded as the combination of the following items : a) Logical structure of document annotated by tags, b) Text, and c) Information extracted by the technology of Information Extraction.
Through the two year research, we obtained the following results :
1. Extraction of structure of intra-documents based on similarity among passages :
By using not only intra-document information but also inter-document information, we improve the effectiveness of retrieving relevant portions of document.
2. Multi-strategic named entity recognizer based on machine learning and extraction patterns :
By combining those two types of strategies for named entity task, we improve the accuracy of recognition of named entities.
3. Extraction of numerical information and its application to Question Answering :
We consider "Question Answering" is the one of the ideal context retrieval system. Named entities correspond to the answer for the 4W-type questions. On the other hand, it is numerical expressions what corresponds to H-type questions. Therefore, we proposed a method to extract numerical expressions with its context as a part of a QA system.
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Report
(3 results)
Research Products
(15 results)
