Interactive and nonparametric modeling of preferences on an ordinal scale using small data

Erişkin L., Köksal G.

EXPERT SYSTEMS WITH APPLICATIONS, vol.65, pp.345-360, 2016 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 65
  • Publication Date: 2016
  • Doi Number: 10.1016/j.eswa.2016.08.063
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.345-360
  • Keywords: Preference modeling, Sorting, Active learning, Interactive approach, Multi criteria decision aid, RECOMMENDER SYSTEM, PERFORMANCE, SUPPORT
  • TED University Affiliated: No


In this study, we consider learning preference structure of a Decision Maker (DM). Many preference modeling problems in a variety of fields such as marketing, quality control and economics involve possibly interacting criteria, and an ordinal scale is used to express preference of objects. In these cases, typically underlying preference structure of the DM and distribution of criteria values are not known, and only a few data can be collected about the preferences of the DM.