A Novel Method of Applying Big Data for Analysis Model of Library User Behavior
Authors
Kaijun Yu, Song Luo, Xuejun Zhou, Rui Wang, Longjie Sun
Corresponding Author
Kaijun Yu
Available Online October 2019.
- DOI
- 10.2991/icoi-19.2019.130How to use a DOI?
- Keywords
- Data mining, Supervised learning, User portrait
- Abstract
A large number of library user behaviour data generated in real time in the era of big data artificial intelligence requires more efficient and scientific analysis technology to help libraries improve the level and quality of personalized services, while the increasingly popular campus Internet of Things system needs to be more Active network security precautions, proactively detect unreliable abnormal behavior of the network and feedback users to improve security awareness. Explores a big data analysis model using traditional data mining and classification learning, which combines user personality analysis and abnormal behavior detection
- Copyright
- © 2019, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Kaijun Yu AU - Song Luo AU - Xuejun Zhou AU - Rui Wang AU - Longjie Sun PY - 2019/10 DA - 2019/10 TI - A Novel Method of Applying Big Data for Analysis Model of Library User Behavior BT - Proceedings of the 2019 International Conference on Organizational Innovation (ICOI 2019) PB - Atlantis Press SP - 742 EP - 745 SN - 2352-5428 UR - https://doi.org/10.2991/icoi-19.2019.130 DO - 10.2991/icoi-19.2019.130 ID - Yu2019/10 ER -