Zobrazeno 1 - 10
of 146
pro vyhledávání: '"Neil Hurley"'
Autor:
Qinqin Wang, Diarmuid Oreilly-Morgan, Elias Z. Tragos, Neil Hurley, Barry Smyth, Aonghus Lawlor, Ruihai Dong
Publikováno v:
IEEE Access, Vol 10, Pp 71961-71972 (2022)
Despite many recent advances, state-of-the-art recommender systems still struggle to achieve good performance with sparse datasets. To address the sparsity issue, transfer learning techniques have been investigated for recommender systems, but they t
Externí odkaz:
https://doaj.org/article/c268e01f9598415e8e0eef74e399636d
Autor:
Bichen Shi, Elias Z. Tragos, Makbule Gulcin Ozsoy, Ruihai Dong, Neil Hurley, Barry Smyth, Aonghus Lawlor
Publikováno v:
IEEE Access, Vol 9, Pp 83340-83354 (2021)
Traditional Recommender Systems (RS) use central servers to collect user data, compute user profiles and train global recommendation models. Central computation of RS models has great results in performance because the models are trained using all th
Externí odkaz:
https://doaj.org/article/2c91b62aeae84cf5a29d7ebb4ac6d23e
Autor:
Makbule Gulcin Ozsoy, Diarmuid O'Reilly-Morgan, Panagiotis Symeonidis, Elias Z. Tragos, Neil Hurley, Barry Smyth, Aonghus Lawlor
Publikováno v:
IEEE Access, Vol 8, Pp 181835-181847 (2020)
Neural network-based recommendation algorithms have become the state-of-the-art in recommender systems and can achieve very high predictive accuracy. However, these models are usually considered as black boxes in terms of their interpretability due t
Externí odkaz:
https://doaj.org/article/b16c2878d31f48808bc2dae531e4a30f
Publikováno v:
Journal of Systemics, Cybernetics and Informatics, Vol 1, Iss 6, Pp 11-17 (2003)
Under perfect synchronisation conditions, watermarking schemes employing asymmetric spread-spectrum techniques are suitable for copy-protection of audio signals. This paper proposes to combine the use of a robust psychoacoustic projection for the ext
Externí odkaz:
https://doaj.org/article/fd8b21a8118947febf156a01491d6052
Social Supports in HE: a Social Network Analysis (SNA) Approach to Understanding Learning Experience
Autor:
Bernadette Brereton, Neil Hurley
Publikováno v:
Irish Journal of Academic Practice, Vol 9, Iss 1
In this study, we combined social network analysis with mixed methods approaches to examine social roles and network patterns in social network data gathered from one complete class group of learners in a higher education setting. We investigated the
Externí odkaz:
https://doaj.org/article/bce7628b39ea4ec89b1b414cbbd1e4e4
Publikováno v:
The International FLAIRS Conference Proceedings. 36
Fashion industry is driven by fashion cycles, in which a fashion item is launched, rises to mainstream appeal and becomes a trend, then diminishes and eventually becomes obsolete. These properties make it critical to incorporate temporal information
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7d7ef20a44de9310fafc6a69530ca5e
https://doi.org/10.32473/flairs.36.133307
https://doi.org/10.32473/flairs.36.133307
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031282430
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::675e56c226628cd3a3b60887e0f94192
https://doi.org/10.1007/978-3-031-28244-7_16
https://doi.org/10.1007/978-3-031-28244-7_16
Publikováno v:
Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc66380f72604e444cc33fd412d20a78
https://doi.org/10.1145/3503252.3531316
https://doi.org/10.1145/3503252.3531316
Autor:
Barry Smyth, Ruihai Dong, Neil Hurley, Aonghus Lawlor, Bichen Shi, Elias Z. Tragos, Makbule Gulcin Ozsoy
Publikováno v:
IEEE Access, Vol 9, Pp 83340-83354 (2021)
Traditional Recommender Systems (RS) use central servers to collect user data, compute user profiles and train global recommendation models. Central computation of RS models has great results in performance because the models are trained using all th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b8a47a439fad77427f986225ae72c60
https://doi.org/10.1109/access.2021.3087406
https://doi.org/10.1109/access.2021.3087406
Autor:
Neil Hurley, Faisal Ghaffar
Publikováno v:
Computational Social Networks, Vol 7, Iss 1, Pp 1-27 (2020)
Strategic network formation is a branch of network science that takes an economic perspective to the creation of social networks, considering that actors in a network form links in order to maximise some utility that they attain through their connect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cc5f7f50496d4b81fde0ed987e819a53
http://link.springer.com/article/10.1186/s40649-020-00079-4
http://link.springer.com/article/10.1186/s40649-020-00079-4