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A Study on Automatic Indexing Based on Textual Mentions to Geographical Location in Story Archiving

Research Project

Project/Area Number 18K11982
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 90020:Library and information science, humanistic and social informatics-related
Research InstitutionUniversity of Tsukuba

Principal Investigator

INUI Takashi  筑波大学, システム情報系, 准教授 (60397031)

Project Period (FY) 2018-04-01 – 2021-03-31
Project Status Completed (Fiscal Year 2020)
Budget Amount *help
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2018: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Keywords文書ジオロケーション / エンティティ・リンキング / 地名抽出 / 固有表現抽出 / Toponym resolution / Bi-LSTM-CRF / 地理的位置推定 / 地理的地位特定 / 自然言語処理 / 条件付確率場 / エンティティリンキング / 地理的位置情報
Outline of Final Research Achievements

This research project aims to develop a document retrieval technology by geographic location by indexing geographic locations mentioned in the document contents. The main research results are as follows. (1) We developed a deep learning-based geographic name extraction model that is especially robust to unknown words by using word information in documents and image information corresponding to words. (2) We developed a model for identifying the real-world geographic location of place names (place name disambiguation) based on word distributions with data expansion focusing on address hierarchy. (3) By integrating the above models, we have developed a technology to automatically identify geographic location information required for indexing geographic locations mentioned in document contents with a certain level of performance.

Academic Significance and Societal Importance of the Research Achievements

本研究課題は、大規模自然災害アーカイブにおいて、従来技術では地理情報システムとの親和性の低かった文書コンテンツに対して、特定の被災地域に限定したコンテンツ検索を実現するための技術開発を目的としたものである。本研究課題で得られた成果を活用することにより、自然災害に対する防災・減災対策や、自然災害からの復旧・復興事業に資する情報へのアクセス効率が従来よりも向上することが期待される。

Report

(4 results)
  • 2020 Annual Research Report   Final Research Report ( PDF )
  • 2019 Research-status Report
  • 2018 Research-status Report
  • Research Products

    (6 results)

All 2021 2020 2019 2018

All Presentation (6 results) (of which Int'l Joint Research: 2 results)

  • [Presentation] ニューラル日本語固有表現認識における格フレームの有効性検証2021

    • Author(s)
      陰山宗一, 駒田拓也, 乾孝司
    • Organizer
      言語処理学会第27回年次大会
    • Related Report
      2020 Annual Research Report
  • [Presentation] An Element-wise Visual-enhanced BiLSTM-CRF Model for Location Name Recognition2020

    • Author(s)
      Takuya Komada and Takashi Inui
    • Organizer
      The 3rd International Workshop on Spatial Language Understanding
    • Related Report
      2020 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 日本語地理的位置推定課題におけるインジケータ付deepgeo法の提案と評価2020

    • Author(s)
      平川冬尉, 乾孝司
    • Organizer
      第34回人工知能学会全国大会
    • Related Report
      2019 Research-status Report
  • [Presentation] 新聞記事中の地名に対する地理的位置推定における有効な素性の調査2019

    • Author(s)
      関龍, 乾孝司
    • Organizer
      第33回人工知能学会全国大会
    • Related Report
      2019 Research-status Report
  • [Presentation] 局所文脈と関連文書を用いた地名に対する地理的位置の同定2018

    • Author(s)
      関龍, 乾孝司
    • Organizer
      第32回人工知能学会全国大会
    • Related Report
      2018 Research-status Report
  • [Presentation] An Analysis of Japanese Named Entity Recognizer Specialized for Person and Organization Entities2018

    • Author(s)
      Takashi Inui and Yuki Nakano
    • Organizer
      The 22nd International Conference on Asian Language Processing
    • Related Report
      2018 Research-status Report
    • Int'l Joint Research

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Published: 2018-04-23   Modified: 2022-01-27  

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