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Estimating Attributed Central Orders

An Empirical Comparison
  • Toshihiro Kamishima
  • Hideto Kazawa
  • Shotaro Akaho
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3201)

Abstract

Lists of ordered objects are widely used as representational forms. Such ordered objects include Web search results or best seller lists. In spite of their importance, the methods of processing orders have received little attention. However, research concerning object ordering is becoming more common. Some researchers have developed various methods to perform almost the same task: a learning function used for sorting objects from examples of ordered sequences. We call this task the estimation of Attributed Central Orders (ACO for short). The performance of this task is useful for sensory surveys, information retrieval, or decision making. We performed a survey of such methods, empirically compared the methods’ properties, and discuss their merits and demerits.

Keywords

Estimation Task Learning Function Attribute Noise Representational Form Sample Order 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Toshihiro Kamishima
    • 1
  • Hideto Kazawa
    • 2
  • Shotaro Akaho
    • 1
  1. 1.National Institute of Advanced Industrial Science and Technology (AIST)Tsukuba, IbarakiJapan
  2. 2.NTT Communication Science LaboratoriesNTT CorporationKyotoJapan

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