Zobrazeno 1 - 10
of 72
pro vyhledávání: '"M, Vijaikumar"'
The personalized list continuation (PLC) task is to curate the next items to user-generated lists (ordered sequence of items) in a personalized way. The main challenge in this task is understanding the ternary relationships among the interacting enti
Externí odkaz:
http://arxiv.org/abs/2110.01467
Cross-Domain Collaborative Filtering (CDCF) provides a way to alleviate data sparsity and cold-start problems present in recommendation systems by exploiting the knowledge from related domains. Existing CDCF models are either based on matrix factoriz
Externí odkaz:
http://arxiv.org/abs/1907.08440
Publikováno v:
Indian Dermatology Online Journal, Vol 14, Iss 3, Pp 357-360 (2023)
Background: Post-exposure prophylaxis (PEP) for occupational human immunodeficiency virus (HIV) exposure involves the comprehensive measures used to prevent transmission of blood-borne pathogens such as HIV, hepatitis B virus, and hepatitis C virus t
Externí odkaz:
https://doaj.org/article/8640862db9a744db8337958b22380837
Autor:
Mohanan, Saritha (AUTHOR), M., Vijaikumar1 (AUTHOR) vijaiderm@gmail.com, Carounanidy, Udayashankar (AUTHOR), C. S., Banushree2 (AUTHOR)
Publikováno v:
Indian Journal of Dermatology, Venereology & Leprology. Jan/Feb2024, Vol. 90 Issue 1, p1-4. 4p.
Akademický článek
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Publikováno v:
Indian Dermatology Online Journal. 14:357
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1da2c6bfd8d7d3abd178447c9a14dc2f
https://doi.org/10.4103/idoj.idoj_496_22
https://doi.org/10.4103/idoj.idoj_496_22
Publikováno v:
SIGIR
Explainable Recommendations provide the reasons behind why an item is recommended to a user, which often leads to increased user satisfaction and persuasiveness. An intuitive way to explain recommendations is by generating a synthetic personalized na
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::19555efc34b23b0c2130a4cacfd87501
https://doi.org/10.1145/3404835.3462939
https://doi.org/10.1145/3404835.3462939
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676575
ECML/PKDD (1)
ECML/PKDD (1)
Cross-Domain Collaborative Filtering (CDCF) provides a way to alleviate data sparsity and cold-start problems present in recommendation systems by exploiting the knowledge from related domains. Existing CDCF models are either based on matrix factoriz
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::785e8e7a4bcf3825eeac1f310ce8443e
https://doi.org/10.1007/978-3-030-67658-2_42
https://doi.org/10.1007/978-3-030-67658-2_42
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676636
ECML/PKDD (3)
ECML/PKDD (3)
Bundle recommendation – recommending a group of products in place of individual products to customers is gaining attention day by day. It presents two interesting challenges – (1) how to personalize and recommend existing bundles to users, and (2
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c390139ac13a4f8d16e43e9379cb636
https://doi.org/10.1007/978-3-030-67664-3_18
https://doi.org/10.1007/978-3-030-67664-3_18
Publikováno v:
Advances in Knowledge Discovery and Data Mining ISBN: 9783030474256
PAKDD (1)
PAKDD (1)
Exploiting heterogeneous information networks (HIN) to top-N recommendation has been shown to alleviate the data sparsity problem present in recommendation systems. This requires careful effort in extracting relevant knowledge from HIN. However, exis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e1e5bf6e5382081372e79c74b88bbca9
https://doi.org/10.1007/978-3-030-47426-3_3
https://doi.org/10.1007/978-3-030-47426-3_3