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Tag Recommendation to Support the Release and Retrieval of Open Government Data

Research Project

Project/Area Number 19K12715
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 InstitutionShimane University

Principal Investigator

Yamada Yasuhiro  島根大学, 学術研究院理工学系, 助教 (50529609)

Project Period (FY) 2019-04-01 – 2024-03-31
Project Status Completed (Fiscal Year 2023)
Budget Amount *help
¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2021: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2020: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2019: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Keywordsオープンデータ / テキストマイニング / タグ推薦 / 機械学習
Outline of Research at the Start

近年,政府や地方自治体が保有する統計データをWeb上に公開する動きが広がっている.このようなデータはオープンデータと呼ばれる.オープンデータを公開する際には,データの内容を表わす語であるタグが付与される.本研究は,政府や自治体がオープンデータを公開する際の支援と,利用者がオープンデータを検索する際の支援を目的として,オープンデータに対してタグを自動付与する手法の開発を行う.

Outline of Final Research Achievements

The purpose of this research is to automatically assign tags (labels) to statistical data published on the Web by the government, which is called open government data. We use multi-label classification, a method that assigns multiple labels to a single dataset. We are particularly interested in infrequent labels in training data and aim to assign them.
Focusing on the simultaneous occurrence of multiple labels in a single dataset, we proposed an oversampling method to increase the training data for labels that appear infrequently. Also, we have developed a system that recommends tags to be assigned to a single dataset when the title or description of the dataset is given as input.

Academic Significance and Societal Importance of the Research Achievements

学習データにおいて出現回数の少ないタグは推薦されにくいという問題に対して,疑似的にそれらの学習データを増やす手法を開発した.また,オープンデータのタイトルや説明を入力したとき,そのオープンデータに対して付与すべきタグを推薦するシステムを開発した.オープンデータを公開する際に,ふさわしいタグを付与することの一助となることが期待できる.また,付与されたタグがオープンデータの検索の際にも役立つことが期待できる.

Report

(6 results)
  • 2023 Annual Research Report   Final Research Report ( PDF )
  • 2022 Research-status Report
  • 2021 Research-status Report
  • 2020 Research-status Report
  • 2019 Research-status Report
  • Research Products

    (5 results)

All 2023 2022 Other

All Journal Article (2 results) (of which Peer Reviewed: 1 results) Presentation (2 results) (of which Int'l Joint Research: 1 results) Remarks (1 results)

  • [Journal Article] Tag Recommendation System for Data Catalog Site of Japanese Government2023

    • Author(s)
      Yamada Yasuhiro
    • Journal Title

      Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2023)

      Volume: 3: KMIS Pages: 325-331

    • DOI

      10.5220/0012260000003598

    • Related Report
      2023 Annual Research Report
    • Peer Reviewed
  • [Journal Article] 政府オープンデータにおける少数ラベルの推定2022

    • Author(s)
      河野湧芽,山田泰寛
    • Journal Title

      2022年度(第73回)電気・情報関連学会中国支部連合大会

      Volume: -

    • Related Report
      2022 Research-status Report
  • [Presentation] Tag Recommendation System for Data Catalog Site of Japanese Government2023

    • Author(s)
      Yamada Yasuhiro
    • Organizer
      15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2023)
    • Related Report
      2023 Annual Research Report
    • Int'l Joint Research
  • [Presentation] 政府オープンデータにおける少数ラベルの推定2022

    • Author(s)
      河野湧芽
    • Organizer
      2022 年度(第73 回)電気・情報関連学会中国支部連合大会
    • Related Report
      2022 Research-status Report
  • [Remarks] 政府・自治体オープンデータ・タグ推薦システム

    • URL

      http://buti.cis.shimane-u.ac.jp/

    • Related Report
      2022 Research-status Report

URL: 

Published: 2019-04-18   Modified: 2025-01-30  

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