Zobrazeno 1 - 10
of 66
pro vyhledávání: '"user preference drift"'
Job recommender systems are crucial for aligning job opportunities with job-seekers in online job-seeking. However, users tend to adjust their job preferences to secure employment opportunities continually, which limits the performance of job recomme
Externí odkaz:
http://arxiv.org/abs/2407.00082
Publikováno v:
IEEE Access, Vol 12, Pp 105831-105849 (2024)
Social and sequential recommendations employing bidirectional attention architecture represent a notable advancement in deep learning, enhancing recommender system performance. This breakthrough facilitates the representation learning of interactions
Externí odkaz:
https://doaj.org/article/2bedcd019a2c4ceead4ec58a63cbe948
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
In Expert Systems With Applications 15 December 2021 185
Publikováno v:
IEEE Access, Vol 8, Pp 86433-86447 (2020)
Recommender systems are efficient tools for online applications; these systems exploit historical user ratings on items to make recommendations of items to users. This paper aims to enhance dynamic collaborative filtering on recommender systems under
Externí odkaz:
https://doaj.org/article/5490c44007a948aeb0fdc19a01ad610d
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
Expert Systems with Applications. 185:115626
Recommender systems are challenging research problems being exploited to suggest new items or services, such as books, music and movies, and even people, to users based on information about the user profile or the recommended items. To date, collabor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7575a5ff56cd0f283adb05b1acb887a6
https://doi.org/10.1016/j.eswa.2021.115626
https://doi.org/10.1016/j.eswa.2021.115626
Publikováno v:
Journal of the China Society for Scientific & Technical Information; Aug2011, Vol. 30 Issue 8, p802-811, 10p
Publikováno v:
Advanced Materials Research. 186:474-478
The knowledge of preference drift is important to maintain the user’s preference accurate. With the swift development of mobile service the recognition of such knowledge has attracted immense attention in recent times. However, existing research ba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::992646519aeb2864ceee15d37161adf3
https://doi.org/10.4028/www.scientific.net/amr.186.474
https://doi.org/10.4028/www.scientific.net/amr.186.474
Publikováno v:
Advanced Materials Research; January 2011, Vol. 186 Issue: 1 p474-478, 5p