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2018 年度 実施状況報告書

Archive-based Question Answering

研究課題

研究課題/領域番号 18K19841
研究機関京都大学

研究代表者

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

研究期間 (年度) 2018-06-29 – 2020-03-31
キーワードquestion answering / document archives
研究実績の概要

We have designed a working demo system to answer queries about similarity of objects across-time. The proposed system allows also for input of a viewpoint to further specify the query. The description of this work was published as a demo paper at WSDM2019 conference.

We have also built the foundations for generic news archive answering system. It uses solr as a search engine and state of the art answer selector based on bi-directional LSTM to extract answers from pool of candidate documents. The main focus was on re-ranking search results returned by solr so that documents that have highest probability of answer are collected. On the corpus of manually created 200 temporal questions we foud out that our reranking approach improves results by 10%.

現在までの達成度 (区分)
現在までの達成度 (区分)

2: おおむね順調に進展している

理由

There is no substantial delay in this project. We plan to submit conference paper further in this year and we will soon release the questions dataset.

今後の研究の推進方策

We will create larger datasets of questions and answers in the near future. Next step assumes incorporation of a supervised approach based on neural networks to improve the computation or extraction of the answer. The decision if the answer should be computed or extracted should be also performed automatically in the future. We will also continue improving the document re-ranking functions to further boost the performance.

次年度使用額が生じた理由

We need to use the grant funds in the next year in order to continue the project. In particular to develop neural network based mechanism for answering questions. This research field is very new and challenging. Developing methods is then quite difficult and needs a lot of effort and manual testing. Furthermore we want to develop large scale test sets for evaluating of developed methods. We will then employ crowdsourcing to gather a lot of questions (around 2000 manually made questions).

  • 研究成果

    (4件)

すべて 2019 2018

すべて 雑誌論文 (4件) (うち国際共著 4件、 査読あり 4件)

  • [雑誌論文] ATAR: Aspect-based Temporal Analog Retrieval System for Document Archives2019

    • 著者名/発表者名
      Yating Zhang, Adam Jatowt, Sourav S Bhowmick, Yuji Matsumoto
    • 雑誌名

      The 12th International Conference on Web Search and Data Mining (WSDM 2019)

      巻: ACM Press ページ: 762-765

    • DOI

      10.1145/3289600.3290613

    • 査読あり / 国際共著
  • [雑誌論文] Towards Recommending Interesting Content in News Archives2018

    • 著者名/発表者名
      I-Chen Hung, Michael Faeber, Adam Jatowt
    • 雑誌名

      The 20th International Conference on Asia-pacific Digital Libraries (ICADL 2018)

      巻: Springer LNCS ページ: 142-146

    • DOI

      10.1007/978-3-030-04257-8_13

    • 査読あり / 国際共著
  • [雑誌論文] System for Category-driven Retrieval of Historical Events2018

    • 著者名/発表者名
      Yasunobu Sumikawa, Adam Jatowt
    • 雑誌名

      The ACM/IEEE Joint Conference on Digital Libraries (JCDL 2018)

      巻: ACM Press ページ: 413-414

    • DOI

      10.1145/3197026.3203888

    • 査読あり / 国際共著
  • [雑誌論文] Every Word has its History: Interactive Exploration and Visualization of Word Sense Evolution2018

    • 著者名/発表者名
      Adam Jatowt, Ricardo Campos, Sourav S. Bhowmick, Nina Tahmasebi, Antoine Doucet
    • 雑誌名

      The 27th International Conference on Information and Knowledge Management (CIKM 2018)

      巻: ACM Press ページ: 1899-1902

    • DOI

      10.1145/3269206.3269218

    • 査読あり / 国際共著

URL: 

公開日: 2019-12-27  

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