| 研究課題/領域番号 |
17H01828
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| 研究機関 | 京都大学 |
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研究代表者 |
Adam Jatowt 京都大学, 情報学研究科, 特定准教授 (00415861)
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| 研究分担者 |
澄川 靖信 首都大学東京, 大学教育センター, 助教 (70756303)
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| 研究期間 (年度) |
2017-04-01 – 2021-03-31
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| キーワード | news archives / digital history / computational history / summarization / entity similarity |
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| 研究実績の概要 |
We have designed, implemented and tested a novel system for a challenging task of comparative summarization in news archives. Specifically, the proposed method applies Integer Linear Programming approach to connect past and present event-describing sentences in order to form a concise summary related to user query. This work appeared as full paper at WSDM2019 conference.
The next research was about finding similar terms from news archives to the input query from the present. We have applied neural network for this problem and developed demo system which was described as demo paper in WSDM2019 conference.
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| 現在までの達成度 (区分) |
現在までの達成度 (区分)
1: 当初の計画以上に進展している
理由
The current progress of the project is going well. There are no delays or any problems related to its execution.
We are working now on improving the summarization system as well as on work for estimating collective memories and historical references in Twitter. We are also proposing typicality based generation of pairs of similar objects: one object from the past and one from present. This approach allows to map a set of terms (e.g., celebrities) from the past with ones from the present.
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| 今後の研究の推進方策 |
In future work we will provide novel techniques for suggesting, reformulating and extending user queries for historical news archives. First, we will provide taxonomy of search intents for document archives and then we will design effective methods towards supporting user search.
The other long-term research goal is to provide effective methods for extracting numerical information from the past by processing raw news data, such as changes in the value of some variables extracted from news archives over time.
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