Efficient Group Pattern Mining Using Data Summarization
Conference Proceeding Article
In group pattern mining, we discover group patterns from a given user movement database based on their spatio-temporal distances. When both the number of users and the logging duration are large, group pattern mining algorithms become very inefficient. In this paper, we therefore propose a spherical location summarization method to reduce the overhead of mining valid 2-groups. In our experiments, we show that our group mining algorithm using summarized data may require much less execution time than that using non-summarized data.
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
Database Systems for Advanced Applications: 9th International Conference, DASFAA 2004, Jeju Island, Korea, March 17-19, 2003: Proceedings
City or Country
Jeju Island, Korea, Mar 17-19
WANG, Yida; LIM, Ee Peng; and HWANG, San-Yih.
Efficient Group Pattern Mining Using Data Summarization. (2004). Database Systems for Advanced Applications: 9th International Conference, DASFAA 2004, Jeju Island, Korea, March 17-19, 2003: Proceedings. 2973, 895-907. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1030