Zobrazeno 1 - 10
of 44
pro vyhledávání: '"Alper Bilge"'
Publikováno v:
IEEE Access, Vol 12, Pp 183230-183251 (2024)
Recommender systems aid users in discovering items of interest across various domains. However, these systems often suffer from popularity bias, disproportionately recommending popular items and neglecting less popular ones that may still appeal to u
Externí odkaz:
https://doaj.org/article/daf443062bd74578b880f622ef05628e
Publikováno v:
PeerJ Computer Science, Vol 9, p e1438 (2023)
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 due to privacy concerns
Externí odkaz:
https://doaj.org/article/cf8f537ede234fc2a9a8834d3e40b352
Publikováno v:
IEEE Access, Vol 10, Pp 52178-52195 (2022)
The exponential increase in energy demands continuously causes high price energy tariffs for domestic and commercial consumers. To overcome this problem, researchers strive to discover effective ways to reduce peak-hour energy demand through off-peak
Externí odkaz:
https://doaj.org/article/438d570dea5f437a8c6ea0be24771798
Autor:
Emre Yalcin, Alper Bilge
Publikováno v:
Engineering Science and Technology, an International Journal, Vol 33, Iss , Pp 101083- (2022)
Collaborative filtering recommendation algorithms are vulnerable against the popularity bias, including the most popular items repeatedly into the produced ranked lists. However, the research on popularity bias focuses solely on the number of times i
Externí odkaz:
https://doaj.org/article/49d00b3fdf174e169eb58d7c62ddacca
Publikováno v:
Elektronika ir Elektrotechnika, Vol 25, Iss 6, Pp 62-69 (2019)
Despite being a challenging research field with many unresolved problems, recommender systems are getting more popular in recent years. These systems rely on the personal preferences of users on items given in the form of ratings and return the prefe
Externí odkaz:
https://doaj.org/article/08da799be62c466ead82ef9cac7d299a
Publikováno v:
IEEE Access, Vol 7, Pp 28863-28885 (2019)
Due to the mutual advantage of small-scale online service providers, they need to collaborate to deliver recommendations based on arbitrarily distributed preference data without jeopardizing their confidentiality. Besides privacy issues, parties also
Externí odkaz:
https://doaj.org/article/eb44692e94bb456aa90c78cb8e93e444
Autor:
Emre Yalcin, ALPER BİLGE
Publikováno v:
Concurrency and Computation: Practice and Experience. 35
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4eac2aa20b54da73ced6f148c04bba38
https://doi.org/10.1002/cpe.7647
https://doi.org/10.1002/cpe.7647
Publikováno v:
2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6bf118cce1f29c0758693804f097d81c
https://doi.org/10.1109/ismsit56059.2022.9932663
https://doi.org/10.1109/ismsit56059.2022.9932663
Publikováno v:
International Journal of Multimedia Information Retrieval. 10:185-198
The cold-start problem is a grand challenge in music recommender systems aiming to provide users with a better and continuous music listening experience. When a new user creates a playlist, the recommender system remains in a cold-start state until e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f603c88b31750fa496352edaaaf8eb44
https://doi.org/10.1007/s13735-021-00214-5
https://doi.org/10.1007/s13735-021-00214-5
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 12:10125-10144
In music recommender systems, automatic playlist continuation is an emerging task that aims to improve users’ listening experience by recommending music in line with their musical taste. The typical approach towards this goal is to identify playlis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1bbc26c642e74afa01aa8ed543154f72
https://doi.org/10.1007/s12652-020-02777-3
https://doi.org/10.1007/s12652-020-02777-3