- Tytuł:
- On explainable fuzzy recommenders and their performance evaluation
- Autorzy:
-
Rutkowski, Tomasz
Łapa, Krystian
Nielek, Radosław - Powiązania:
- https://bibliotekanauki.pl/articles/330650.pdf
- Data publikacji:
- 2019
- Wydawca:
- Uniwersytet Zielonogórski. Oficyna Wydawnicza
- Tematy:
-
recommender system
explainable recommendation
fuzzy system
Akaike information criterion
system rekomendacyjny
system rozmyty
kryterium informacyjne Akaike - Opis:
- This paper presents a novel approach to the design of explainable recommender systems. It is based on the Wang–Mendel algorithm of fuzzy rule generation. A method for the learning and reduction of the fuzzy recommender is proposed along with feature encoding. Three criteria, including the Akaike information criterion, are used for evaluating an optimal balance between recommender accuracy and interpretability. Simulation results verify the effectiveness of the presented recommender system and illustrate its performance on the MovieLens 10M dataset.
- Źródło:
-
International Journal of Applied Mathematics and Computer Science; 2019, 29, 3; 595-610
1641-876X
2083-8492 - Pojawia się w:
- International Journal of Applied Mathematics and Computer Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł