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Now showing items 11-20 of 25
End to End Invoice Processing Application Based on Key Fields Extraction
(IEEE, 2022)
In this paper, an automatic invoice processing system, which is in great demand among private and public companies, was proposed. The proposed system supports all invoice file types that can be submitted by companies. ...
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 ...
The Unfairness of Collaborative Filtering Algorithms’ Bias Towards Blockbuster Items
(Ocak, 2023)
It is known that collaborative filtering recommendation algorithms are usually biased towards some particular items (e.g., popular) in their produced ranked lists. In this study, we evaluate this problem from the perspective ...
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 ...
LVQ Treatment for Zero-Shot Learning
(Tubitak Academic Journals, 23.01.2023)
In image classification, there are no labeled training instances for some classes, which are therefore called unseen classes or test classes. To classify these classes, zero-shot learning (ZSL) was developed, which typically ...
Zero-shot learning via self-organizing maps
(Springer, 25.01.2023)
Collecting-labeled images from all possible classes related to the task at hand is highly impractical and may even be impossible. At this point, Zero-Shot Learning (ZSL) can enable the classification of new test classes ...
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 ...