Filling-in Missing Objects in Orders

  • Authors:

  • Toshihiro Kamishima;Shotaro Akaho

  • Affiliations:

  • National Institute of Advanced Industrial Science and Technology (AIST), Japan;National Institute of Advanced Industrial Science and Technology (AIST), Japan

  • Venue:
  • ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

Filling-in techniques are important, since missing values frequently appear in real data. Such techniques have been established for categorical or numerical values. Though lists of ordered objects are widely used as representational forms (e.g., Web search results, best-seller lists), filling-in techniques for orders have received little attention. We therefore propose a simple but effective technique to fill-in missing objects in orders. We built this technique into our collaborative filtering system.