• DocumentCode
    2865866
  • Title

    Supervised ordering - an empirical survey

  • Author

    Kamishima, Toshihiro ; Kazawa, Hideto ; Akaho, Shotaro

  • Author_Institution
    Nat. Inst. of Adv. Ind. Sci. & Technol., Japan
  • fYear
    2005
  • fDate
    27-30 Nov. 2005
  • Abstract
    Ordered lists of objects are widely used as representational forms. Such ordered objects include Web search results or bestseller lists. In spite of their importance, methods of processing orders have received little attention. However, research concerning orders has become common; in particular, researchers have developed various methods for the task of supervised ordering to acquire functions for object sorting from example orders. Here, we give a unified view of these methods and our new one, and empirically survey their merits and demerits.
  • Keywords
    learning (artificial intelligence); sorting; object sorting; ordered lists; ordered object; supervised ordering; Communication industry; Data mining; Laboratories; Marketing and sales; Random variables; Search engines; Sorting; Telegraphy; Telephony; Web search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Mining, Fifth IEEE International Conference on
  • ISSN
    1550-4786
  • Print_ISBN
    0-7695-2278-5
  • Type

    conf

  • DOI
    10.1109/ICDM.2005.138
  • Filename
    1565754