Cross-Domain User Profile Construction by Log Analysis
- Resource Type
- Conference
- Authors
- Tao, Ye; Wang, Yanzhe; Shi, Cao; Wang, Xiaodong; Xu, Canhui; Xu, Zhifang
- Source
- 2019 IEEE Fourth International Conference on Data Science in Cyberspace (DSC) DSC Data Science in Cyberspace (DSC), 2019 IEEE Fourth International Conference on. :217-221 Jun, 2019
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Information science
Computational modeling
Ubiquitous computing
Conferences
Data science
Cyberspace
Computer science
heterogenous data integration, user profile modeling, semantic activity space, log analysis
- Language
This paper presents a user profile construction approach by analyzing user action log data obtained from cross-domain platforms. The concept of Semantic Activity Space was proposed to represent user characteristics from multiple dimensions, where the basic attributes and values are calculated and integrated from the logs. Non-parametric methods are used to classify and visualize the differences in level and type of activity preferences of users. Log items are integrated from heterogeneous modules of information management systems in manufacturing enterprises. The experiment results indicate that by extracting and analyzing key features from semantic activity space, the characters of a typical user can be properly profiled.