Interactive Summarization System to Support Literature Survey
Project/Area Number |
16K12546
|
Research Category |
Grant-in-Aid for Challenging Exploratory Research
|
Allocation Type | Multi-year Fund |
Research Field |
Library and information science/Humanistic social informatics
|
Research Institution | National Institute of Informatics |
Principal Investigator |
Aizawa Akiko 国立情報学研究所, コンテンツ科学研究系, 教授 (90222447)
|
Co-Investigator(Kenkyū-buntansha) |
徳永 健伸 東京工業大学, 情報理工学院, 教授 (20197875)
|
Project Period (FY) |
2016-04-01 – 2019-03-31
|
Project Status |
Completed (Fiscal Year 2018)
|
Budget Amount *help |
¥3,510,000 (Direct Cost: ¥2,700,000、Indirect Cost: ¥810,000)
Fiscal Year 2017: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2016: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
|
Keywords | 情報組織化 / レビューマトリックス / 文書要約 / 質問応答システム / 文検索 |
Outline of Final Research Achievements |
Scientific literature survey is time-consuming and difficult for researchers and engineers who need to grasp the trends of specific research topics. In many cases, necessary information is not written in the abstracts, and users are enforced to read through the entire papers. One of the conventional practices is to generate a review matrix that organizes the information-in-need in a table format. This research aims at supporting the users’ creation of review matrices. In our study, we developed a method for automatically summarizing multiple articles for a given query. We also constructed a dataset for evaluation and verified the effectiveness of the proposed method.
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Academic Significance and Societal Importance of the Research Achievements |
ユーザの理解支援の研究においては、自動評価が容易に行えるタスクの設計が研究の重要な手段となる。本研究では、レビューマトリックスの作成というタスクを設定することで効率的にデータセットが作成できることを示した。また、支援に必要となる要素技術として自動要約や機械読解の先端技術の研究に取り組み、当該タスクにおける有効性を示した。
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Report
(4 results)
Research Products
(6 results)