Search
Now showing items 11-19 of 19
Aggregating user preferences in group recommender systems: A crowdsourcing approach
(Elsevier, 2022)
We present that group recommendations are similar to crowdsourcing, where the responses of different crowd workers are aggregated in the absence of ground truth. With this in mind, we mimic the use of the EM algorithm as ...
Popularity bias in personality perspective: An analysis of how personality traits expose individuals to the unfair recommendation
(Wiley, Şubat, 202)
Recommender systems are subject to well-known popularity bias issues, that is, they expose frequently rated items more in recommendation lists than less-rated ones. Such a problem could also have varying effects on users ...
A survey of smart home energy conservation techniques
(Elsevier, Mart, 2023)
Smart homes are equipped with easy-to-interact interfaces, providing a more comfortable living environment and less energy consumption. There are currently satisfactory approaches proposed to deliver adequate comfort and ...
A novel classification‐based shilling attack detection approach for multi‐criteria recommender systems
(Wiley, Mayıs, 202)
Recommender systems are emerging techniques guiding individuals with provided referrals by considering their past rating behaviors. By collecting multi-criteria preferences concentrating on distinguishing perspectives of ...
Robustness of privacy-preserving collaborative recommenders against popularity bias problem
(PeerJ, Temmuz, 20)
Recommender systems have become increasingly important in today’s digital age, but they are not without their challenges. One of the most significant challenges is that users are not always willing to share their preferences ...
Improving Brain Tumor Classification with Deep Learning Using Synthetic Data
(Tech Science Press, 2023)
Deep learning (DL) techniques, which do not need complex pre-processing and feature analysis, are used in many areas of medicine and achieve promising results. On the other hand, in medical studies, a limited dataset ...
A Novel Contour Tracing Algorithm for Object Shape Reconstruction Using Parametric Curves
(Tech Science Press, 2023)
Parametric curves such as Bézier and B-splines, originally developed for the design of automobile bodies, are now also used in image processing and computer vision. For example, reconstructing an object shape in an image, ...
Deep learning prediction of motor performance in stroke individuals using neuroimaging data
(Elsevier Science Direct, 2023)
The degree of motor impairment and profile of recovery after stroke are difficult to predict for each individual. Measures obtained from clinical assessments, as well as neurophysiological and neuroimaging techniques have ...
Determination of Photonuclear Reaction Cross-Sections on Stable P-shell Nuclei by Using Deep Neural Networks
(Springer, 13 Mayıs 2)
Photonuclear reactions are widely used in investigations of nuclear structure. Thus, the determination of the cross-sections are essential for the experimental studies. In the present work, (γ, n) photonuclear reaction ...