Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Makbule Gulcin Ozsoy"'
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:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-1 (2018)
Following publication of the original article [1], the authors reported that there was an error in the spelling of the name of one of the authors.
Externí odkaz:
https://doaj.org/article/cd08ac3c408b413eb3d860db8d45884d
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, Barry Smyth, Diarmuid O'Reilly-Morgan, Panagiotis Symeonidis, Aonghus Lawlor, Elias Z. Tragos, Makbule Gulcin Ozsoy
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://explore.openaire.eu/search/publication?articleId=doi_dedup___::b0ae46b99e8add6f9db9642d09658ce4
https://doi.org/10.1109/access.2020.3028587
https://doi.org/10.1109/access.2020.3028587
Autor:
Bichen Shi, Makbule Gulcin Ozsoy, James R. Geraci, Aonghus Lawlor, Elias Z. Tragos, Neil Hurley, Barry Smyth
Publikováno v:
RecSys
Recommender systems (RS) share many features and objectives with reinforcement learning (RL) systems. The former aim to maximise user satisfaction by recommending the right items to the right users at the right time, the latter maximise future reward
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76598de357190c2662356b64a45a1f40
https://doi.org/10.1145/3298689.3346981
https://doi.org/10.1145/3298689.3346981
WOS: 000468739200001 In this paper, we introduce a method based on recommendation systems to predict the structure of Gene Regulatory Networks (GRNs) making use of data from multiple sources. Our method is based on collaborative filtering approach en
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8262ec0f7df8c38689d5e3280eee9293
https://aperta.ulakbim.gov.tr/record/112314
https://aperta.ulakbim.gov.tr/record/112314
Publikováno v:
Applied Intelligence. 45:1047-1065
It is becoming a common practice to use recommendation systems to serve users of web-based platforms such as social networking platforms, review web-sites, and e-commerce web-sites. Each platform produces recommendations by capturing, maintaining and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ae18b77b52198839790018b5573a004
https://doi.org/10.1007/s10489-016-0803-1
https://doi.org/10.1007/s10489-016-0803-1
Publikováno v:
Journal of Information Science. 37:405-417
Text summarization solves the problem of presenting the information needed by a user in a compact form. There are different approaches to creating well-formed summaries. One of the newest methods is the Latent Semantic Analysis (LSA). In this paper,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80b0848ed47b964a9bc3e2e2960dd17e
https://doi.org/10.1177/0165551511408848
https://doi.org/10.1177/0165551511408848
Publikováno v:
BMC Bioinformatics, Vol 19, Iss 1, Pp 1-1 (2018)
BMC Bioinformatics
BMC Bioinformatics
Background Drug repositioning is the process of identifying new targets for known drugs. It can be used to overcome problems associated with traditional drug discovery by adapting existing drugs to treat new discovered diseases. Thus, it may reduce a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9a6c77a1b2a65e67acdf059897403142
http://link.springer.com/article/10.1186/s12859-018-2258-3
http://link.springer.com/article/10.1186/s12859-018-2258-3