Improving Pairwise Preference Mining Algorithms Using Preference Degrees

Authors

  • Juliete A. Ramos Costa No affiliation declared
  • Sandra de Amo UFU

DOI:

https://doi.org/10.5753/jidm.2016.1580

Keywords:

data mining, fuzzy preference, preference mining

Abstract

Different preference mining techniques designed to predict a preference order on objects have been proposed in the literature, with very good accuracy results. In this paper, we propose to consider not only the fact that the user prefer an item i1 to an item i2 but also the degree  of his preference on the two items.  We propose the algorithm FuzzyPrefMiner designed to predict fuzzy preferences and show through a series of experiments that it outperforms  pairwise preference mining techniques whose  training phase do not include information on preference degrees.

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Published

2017-02-03

How to Cite

A. Ramos Costa, J., & de Amo, S. (2017). Improving Pairwise Preference Mining Algorithms Using Preference Degrees. Journal of Information and Data Management, 7(2), 86. https://doi.org/10.5753/jidm.2016.1580

Issue

Section

Regular Papers