Recommending scientific papers through a method based on bibliometric measures
Authors
Álvaro Tejada-Lorente, Carlos Porcel, Juan Bernabé-Moreno, Enrique Herrera-Viedma
Corresponding Author
Álvaro Tejada-Lorente
Available Online June 2015.
- DOI
- 10.2991/ifsa-eusflat-15.2015.72How to use a DOI?
- Keywords
- Recommender systems, item quality, fuzzy linguistic modeling, papers recommendation
- Abstract
We present a quality-based fuzzy linguistic recommender system for researchers. We propose the use of some bibliometrics measures as the way to quantify the quality of both items and users. The system takes into account the measured quality as the main factor for the re-ranking of the top-N recommendations list in order to point researchers to the latest and the best papers in their domain. To prove the accuracy improvement, we conduct a study involving different recommendation approaches. The results obtained proved to be satisfactory within the research departments who took part on the tests.
- 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 - Álvaro Tejada-Lorente AU - Carlos Porcel AU - Juan Bernabé-Moreno AU - Enrique Herrera-Viedma PY - 2015/06 DA - 2015/06 TI - Recommending scientific papers through a method based on bibliometric measures 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 - 498 EP - 505 SN - 1951-6851 UR - https://doi.org/10.2991/ifsa-eusflat-15.2015.72 DO - 10.2991/ifsa-eusflat-15.2015.72 ID - Tejada-Lorente2015/06 ER -