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Investigating and counteracting popularity bias in group recommendations
(Elsevier, 2021)
Popularity bias is an undesirable phenomenon associated with recommendation algorithms where popular items tend to be suggested over long-tail ones, even if the latter would be of reasonable interest for individuals. Such ...
An entropy empowered hybridized aggregation technique for group recommender systems
(Elsevier, 15.03.2021)
Group recommender systems aim to suggest appropriate products/services to a group of users rather than individuals. These recommendations rely solely on determining group preferences, which is accomplished by an aggregation ...
Synthesis, stability, density, viscosity of ethylene glycol-based ternary hybrid nanofluids: Experimental investigations and model-prediction using modern machine learning techniques
(22.02.2022)
A direct sol-gel technique was utilized to produce rGO-Fe3O4-TiO2 ternary hybrid nanocomposites to produce ethylene glycol (EG) based stable nanofluids, characterized by energy-dispersive X-ray, X-ray dispersion, Fourier ...
An investigation of the effect of acrylamide on fracture healing in rats.
(14.02.2022)
ABSTRACT
BACKGROUND: The aim of this study was to investigate the effects of acrylamide (AA) on fracture healing histologically, biochemically, and radiologically in a rat femur fracture model.
METHODS: Scanning electron ...
Long term electricity load forecasting based on regional load model using optimization techniques: A case study
(Taylor&Francis, 2022)
Long-term load forecasting is a significant and complex topic in electric
distribution systems. Forecasters is need to proper forecasting methodologies
and smart solutions to minimize complexity. In this study, regional ...