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Umemoto Kazutoshi  梅本 和俊

ORCIDConnect your ORCID iD *help
Researcher Number 90783217
Other IDs
Affiliation (based on the past Project Information) *help 2020 – 2024: 東京大学, 生産技術研究所, 助教
2018 – 2019: 国立研究開発法人情報通信研究機構, 統合ビッグデータ研究センターソーシャルビッグデータ研究連携センター, 研究員
2017: 国立研究開発法人情報通信研究機構, 統合ビッグデータ研究センター, 研究員
Review Section/Research Field
Principal Investigator
Basic Section 62020:Web informatics and service informatics-related / Web informatics, Service informatics
Keywords
Principal Investigator
推薦システム / 機械忘却 / 系列型推薦 / ユーザ行動 / スキルアップ / スキル上達 / 情報推薦 / 態度変容 / 行動選択 / ウェブマイニング / 情報検索
  • Research Projects

    (3 results)
  • Research Products

    (8 results)
  •  忘却可能な系列型推薦システムに関する研究Principal Investigator

    • Principal Investigator
      梅本 和俊
    • Project Period (FY)
      2023 – 2025
    • Research Category
      Grant-in-Aid for Scientific Research (C)
    • Review Section
      Basic Section 62020:Web informatics and service informatics-related
    • Research Institution
      The University of Tokyo
  •  A Study on Recommender Systems for Improving User SkillsPrincipal Investigator

    • Principal Investigator
      Umemoto Kazutoshi
    • Project Period (FY)
      2020 – 2022
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 62020:Web informatics and service informatics-related
    • Research Institution
      The University of Tokyo
  •  Searching for Information That Can Change People's Opinions and BehaviorsPrincipal Investigator

    • Principal Investigator
      Umemoto Kazutoshi
    • Project Period (FY)
      2017 – 2020
    • Research Category
      Grant-in-Aid for Young Scientists (B)
    • Research Field
      Web informatics, Service informatics
    • Research Institution
      The University of Tokyo
      National Institute of Information and Communications Technology

All 2022 2021 2020 2018 2017

All Journal Article Presentation

  • [Journal Article] 実世界での行動に影響を与える情報のソーシャルメディアからの発見2018

    • Author(s)
      梅本和俊, 豊田正史
    • Journal Title

      日本データベース学会和文論文誌

      Volume: 16-J

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-17K12787
  • [Journal Article] Search by Screenshots for Universal Article Clipping in Mobile Apps2017

    • Author(s)
      Kazutoshi Umemoto, Ruihua Song, Jian-Yun Nie, Xing Xie, Katsumi Tanaka, and Yong Rui
    • Journal Title

      ACM Transactions on Information Systems

      Volume: 35 Issue: 4 Pages: 1-29

    • DOI

      10.1145/3091107

    • Peer Reviewed / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17K12787, KAKENHI-PROJECT-15H01718
  • [Presentation] ML-1M++: MovieLens-Compatible Additional Preferences for More Robust Offline Evaluation of Sequential Recommenders2022

    • Author(s)
      Kazutoshi Umemoto
    • Organizer
      The 31st ACM International Conference on Information & Knowledge Management (CIKM 2022)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K19935
  • [Presentation] 好奇心に駆られたユーザ行動研究のつまみ食い2022

    • Author(s)
      梅本 和俊
    • Organizer
      WebDB夏のワークショップ2022
    • Invited
    • Data Source
      KAKENHI-PROJECT-20K19935
  • [Presentation] スキル向上を可能とする推薦の実現に向けた行動系列におけるユーザ成長とアイテム難易度のモデル化2021

    • Author(s)
      梅本和俊, Tova Milo, 喜連川優
    • Organizer
      第20回情報科学技術フォーラム(FIT 2021)
    • Invited
    • Data Source
      KAKENHI-PROJECT-20K19935
  • [Presentation] Toward Recommendation for Upskilling: Modeling Skill Improvement and Item Difficulty in Action Sequences2020

    • Author(s)
      Kazutoshi Umemoto, Tova Milo, and Masaru Kitsuregawa
    • Organizer
      The 36th IEEE International Conference on Data Engineering (ICDE 2020)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17K12787
  • [Presentation] Search by Screenshots for Article Clipping across Mobile Apps2018

    • Author(s)
      Kazutoshi Umemoto
    • Organizer
      The 13th Korea-Japan (Japan-Korea) Database Workshop 2018 (KJDB2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17K12787
  • [Presentation] Search by screenshots for universal article clipping in mobile apps (TOIS)2018

    • Author(s)
      Kazutoshi Umemoto, Ruihua Song, Jian-Yun Nie, Xing Xie, Katsumi Tanaka, and Yong Rui
    • Organizer
      The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17K12787

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