• 专利标题: GRAPH EXPLAINABLE ARTIFICIAL INTELLIGENCE CORRELATION
  • 申请号: EP22213801.8
    申请日: 2022-12-15
  • 公开(公告)号: EP4227855A1
    公开(公告)日: 2023-08-16
  • 发明人: McThrow, MichaelUchino, Kanji
  • 申请人: Fujitsu Limited
  • 申请人地址: JP Kawasaki-shi, Kanagawa 211-8588 1-1, Kamikodanaka 4-chome Nakahara-ku
  • 代理机构: Hoffmann Eitle
  • 优先权: US202217669712 20220211
  • 主分类号: G06N3/04
  • IPC分类号: G06N3/04 G06N3/10 G06N5/045
GRAPH EXPLAINABLE ARTIFICIAL INTELLIGENCE CORRELATION
摘要:
A method may include obtaining a first result of a graph explainable artificial intelligence (GXAI) classification analysis of a dataset of graph-structured data and a second result of a graph analysis algorithm that represents relationships between elements of the dataset. The method may include determining a correlation between the first result and the second result and generating a display within a graphical user interface (GUI) that visualizes similarities between the first result and the second result based on the correlation. Determining the correlation between the first result and the second result may include generating a first vector of the first result of the classification analysis using GXAI techniques and a second vector of the second result of the graph analysis algorithm. A Pearson correlation coefficient or a cosine similarity coefficients may be computed based on the first vector and the second vector in which the computed coefficients are indicative of the correlation.
信息查询
0/0