Learning experts’ preferences from informetric data
Authors
Marek Gagolewski, Jan Lasek
Corresponding Author
Marek Gagolewski
Available Online June 2015.
- DOI
- 10.2991/ifsa-eusflat-15.2015.70How to use a DOI?
- Keywords
- Preference learning, fuzzy relations, informetrics, aggregation, h-index
- Abstract
In the field of informetrics, agents are often represented by numeric sequences of non necessarily conforming lengths. There are numerous aggregation techniques of such sequences, e.g., the g-index, the h-index, that may be used to compare the output of pairs of agents. In this paper we address a question whether such impact indices may be used to model experts’ preferences accurately.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Marek Gagolewski AU - Jan Lasek PY - 2015/06 DA - 2015/06 TI - Learning experts’ preferences from informetric data BT - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 484 EP - 491 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.70 DO - 10.2991/ifsa-eusflat-15.2015.70 ID - Gagolewski2015/06 ER -