研究内容/researchResearch Topics

We propose approaches based on probability statistics, signal processing, and machine learning to analyze and support intellectual creation activities.

  • Image Processing

    Image processing

  • Multimedia Retrieval

    Multimedia Retrieval

    We are conducting sentiment analysis and popularity prediction of multimedia contents. We are also studying classification and retrieval methods for data in specific domains such as map images and fashion images.

    • Classification of map images [Sawada&Katsurai, ICASSP2020]
    • Popularity prediction of recipe images [Sanjo&Katsurai, CIKM2017]
    • Image sentiment analysis [Katsurai&Satoh, ICASSP2016]
  • Microblog Analysis

    マイクロブログ分析

    We propose a method for automatically assigning emotion scores to words not included in general dictionaries (e.g. pictographs and slangs).

    • Emoji sentiment dictionary [Kimura&Katsurai, FAB2017(ASONAM2017)]
    • Comparison of Emoji between Japanese and English tweets [Kimura&Katsurai, iiWAS2018]
  • Linked Data

    リンクトデータ

    Relating data on the web to each other is a fundamental technique for knowledge discovery and machine learning. We are currently working on the automatic linking of records between different databases.

    • Multilingual author matching [Chikazawa, Katsurai, Ohmukai, Scientometrics, 2021]
    • Author matching [Katsurai&Ohmukai, JCDL2019]
  • Researcher Topic Analysis

    研究者トピック分析

    The system estimates the researcher's expert topic from the text of the article title, keywords, and abstract, and applies it to the search of related researchers and author identification.

    • Researcher search system [Takahashi, Tango, Chikazawa, &Katsurai, ICADL2020]
    • Extraction of researchers' topics [Katsurai+, IEICETrans, 2016]
  • Social Network Analysis

    ソーシャルネットワーク分析

    Social networks represent the structure of collaboration in intellectual creative activities. We analyze the activity within communities and the differences between communities.

    • Analysis of the current state of collaboration within research institutions [Araki, Katsurai+, IEICE Trans, 2017]
  • Trend Mapping

    トレンドマッピング

    Knowing people's interests helps in strategy development and marketing. We analyze large amounts of data to extract and visualize prevailing topics.

    • Research trend visualization [Katsurai&Ono, Scientometrics, 2019]

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