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2020 Fiscal Year Final Research Report

Archive-based Question Answering

Research Project

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Project/Area Number 18K19841
Research Category

Grant-in-Aid for Challenging Research (Exploratory)

Allocation TypeMulti-year Fund
Review Section Medium-sized Section 62:Applied informatics and related fields
Research InstitutionKyoto University

Principal Investigator

Jatowt Adam  京都大学, 情報学研究科, 特定准教授 (00415861)

Project Period (FY) 2018-06-29 – 2021-03-31
Keywordsnews archives / language change / question answering
Outline of Final Research Achievements

We have developed approaches for answering question in long-term news archives. Our method can answer arbitrary user query about the past by extracting content from news articles that were published long time ago. This is challenging task due to many repeating and periodical events. For this research we have built a small dataset of 1k questions that contain answers. Our approaches are unsupervised and are based on estimating question time scope and then on retrieving content from news archives that fall within or relates to that time scope. After search result reranking using special module answers are produced from individual pages and are aggregated. During the research progress we found out several important observations such as how to find the time scope in the best way or how to combine document relevance with temporal relevance of documents. We have published a paper in core A ranked conference and a journal paper that was invited from that conference submission.

Free Research Field

Natural language processing

Academic Significance and Societal Importance of the Research Achievements

Based on the proposed approaches users can send questions to the past and obtain detailed information without the need to manually search and browse large news article archives. Journalists, historians and anyone who wishes to obtain answers about the past can benefit from this research.

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Published: 2022-01-27  

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