• DocumentCode
    3723097
  • Title

    A Clustering-Based Approach to the Mining of Analogical Proportions

  • Author

    William Correa Beltran;Helene Jaudoin;Olivier Pivert

  • Author_Institution
    IRISA/Shaman, Univ. of Rennes 1, Lannion, France
  • fYear
    2015
  • Firstpage
    125
  • Lastpage
    131
  • Abstract
    This paper presents an approach aimed at mining a new type of pattern in data, namely analogical proportions. An analogical proportion expresses the equality of the relationships between the attributes of two pairs of structured objects. This notion is investigated in the database context for the discovery of different forms of "parallels" between pairs of tuples. First, we give a formal definition of the analogical proportion in the setting of relational databases. Then we focus on the problem of mining analogical proportions. We propose to use a clustering approach for enumerating parallels occurring in a relation, thus discovering analogical proportions.
  • Keywords
    "Data mining","Relational databases","Distortion","Animals","Connectors","Market research"
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2015 IEEE 27th International Conference on
  • ISSN
    1082-3409
  • Type

    conf

  • DOI
    10.1109/ICTAI.2015.31
  • Filename
    7372127