Skip to content
Publish & Distribute
Publishing Solutions
Distribution Solutions
Library Services
Subjects
Architecture and Design
Arts
Business and Economics
Chemistry
Classical and Ancient Near Eastern Studies
Computer Sciences
Cultural Studies
Engineering
General Interest
Geosciences
History
Industrial Chemistry
Jewish Studies
Law
Library and Information Science, Book Studies
Life Sciences
Linguistics and Semiotics
Literary Studies
Materials Sciences
Mathematics
Medicine
Music
Pharmacy
Philosophy
Physics
Social Sciences
Sports and Recreation
Theology and Religion
Publications
Journals
Books
Proceedings
Publishers
Journal Matcher
Blog
Contact
Search
English
English
Deutsch
Polski
Español
Français
Italiano
Cart
Home
Journals
Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
Open Access
Data-driven innovation in university library management and service models
Yan Li
Yan Li
Suzhou University of Science and Technology
Suzhou, China
Search for this author on
Sciendo
|
Google Scholar
Li, Yan
,
Shaoqun Wu
Shaoqun Wu
Party School of Huangshan C.P.C Municipal Committee
Huangshan, China
Search for this author on
Sciendo
|
Google Scholar
Wu, Shaoqun
and
Zhengang Zhu
Zhengang Zhu
Suzhou University of Science and Technology
Suzhou, China
Search for this author on
Sciendo
|
Google Scholar
Zhu, Zhengang
Jan 31, 2024
Applied Mathematics and Nonlinear Sciences
Volume 9 (2024): Issue 1 (January 2024)
About this article
Previous Article
Next Article
Abstract
References
Authors
Articles in this Issue
Preview
PDF
Cite
Share
Download Cover
Published Online:
Jan 31, 2024
Received:
Dec 20, 2023
Accepted:
Dec 25, 2023
DOI:
https://doi.org/10.2478/amns-2024-0229
Keywords
Apriori association rule algorithm
,
Information mining
,
Scheduling optimization
,
Data-driven
,
Library management
© 2024 Yan Li et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
