Research on User Profiling Construction of University Researchers
Based on Institutional Knowledge Base
Authors
Xiaoying Cheng1, Na Zhang2, *
1Experimental Training Base, National University of Defense Technology, Shaanxi, Xi’an, China
2College of Information and Communication, National University of Defense Technology, Hubei, Wuhan, China
*Corresponding author.
Email: 359531099@qq.com
Corresponding Author
Na Zhang
Available Online 9 December 2024.
- DOI
- 10.2991/978-2-38476-309-2_53How to use a DOI?
- Keywords
- University library; User profiling; Institutional knowledge base; Researchers
- Abstract
Based on the analysis of the characteristics of scientific research personnel’s knowledge needs, a model for constructing university scientific research personnel portraits based on institutional knowledge bases is proposed to meet the practical needs of scientific research personnel portraits. This model accelerates the implementation of scientific research personnel portraits, promotes the transformation and development of university institutional knowledge bases, and enhances the core competitiveness of libraries.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Xiaoying Cheng AU - Na Zhang PY - 2024 DA - 2024/12/09 TI - Research on User Profiling Construction of University Researchers BT - Proceedings of the 2024 9th International Conference on Modern Management, Education and Social Sciences (MMET 2024) PB - Atlantis Press SP - 432 EP - 438 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-309-2_53 DO - 10.2991/978-2-38476-309-2_53 ID - Cheng2024 ER -