Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Alireza Gharahighehi"'
Publikováno v:
IEEE Access, Vol 10, Pp 117189-117198 (2022)
The cold-start problem is one of the main challenges in recommender systems and specifically in collaborative filtering methods. Such methods, albeit effective, typically can not handle new items or users that do not have any prior interaction activi
Externí odkaz:
https://doaj.org/article/50e4a7ca5b0744a784d07155d2e408c7
Publikováno v:
Applied Sciences, Vol 11, Iss 16, p 7502 (2021)
The shift to e-commerce has changed many business areas. Real estate is one of the applications that has been affected by this modern technological wave. Recommender systems are intelligent models that assist users of real estate platforms in finding
Externí odkaz:
https://doaj.org/article/0172be4495924925baaccd581a34aa4d
Publikováno v:
Digital Health, Vol 2 (2016)
This article presents a method by which performances at an emergency department (ED) in a large hospital in Iran could be improved, where the long waiting times and unbalanced utilization create problems for patients and ED staff. This method firstly
Externí odkaz:
https://doaj.org/article/cc4b923599a14aca9957a99aaa6be681
Publikováno v:
Lecture Notes in Networks and Systems ISBN: 9783031160714
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac523210756b825bb09460359b810114
https://doi.org/10.1007/978-3-031-16072-1_39
https://doi.org/10.1007/978-3-031-16072-1_39
Autor:
Alireza Gharahighehi, Celine Vens
One of the most important concerns about recommender systems is the filter bubble phenomenon. While recommender systems try to personalize information, they tighten the filter bubble around the users and deprive them of a wide range of content. To ov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fcde33d0cac07f53da0f23b0206b65fd
https://lirias.kuleuven.be/handle/123456789/663316
https://lirias.kuleuven.be/handle/123456789/663316
Autor:
Alireza Gharahighehi, Celine Vens
Recommender systems are widely applied in digital platforms such as news websites to personalize services based on user preferences. In news websites most of users are anonymous and the only available data is sequences of items in anonymous sessions.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5ba8943be869bb0c156f9dc387bcfdc8
Publikováno v:
Discovery Science ISBN: 9783030889418
DS
DS
Recommender systems are designed to predict user preferences over collections of items. These systems process users’ previous interactions to decide which items should be ranked higher to satisfy their desires. An ensemble recommender system can ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::258d27e38c4721da52d1e1eb1673ce89
https://lirias.kuleuven.be/handle/123456789/682755
https://lirias.kuleuven.be/handle/123456789/682755
Recommender systems are typically designed to fulfill end user needs. However, in some domains the users are not the only stakeholders in the system. For instance, in a news aggregator website users, authors, magazines as well as the platform itself
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd1c452abda8d34c61573f0b8378a12a
Publikováno v:
Digital Health, Vol 2 (2016)
Digital health
Digital health
This article presents a method by which performances at an emergency department (ED) in a large hospital in Iran could be improved, where the long waiting times and unbalanced utilization create problems for patients and ED staff. This method firstly
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aec3a4cd797e1c65ae74bc6f2b31dc33
https://doaj.org/article/cc4b923599a14aca9957a99aaa6be681
https://doaj.org/article/cc4b923599a14aca9957a99aaa6be681