Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
5-2005
Abstract
In this paper, we present a group pattern mining approach to derive the grouping information of mobile device users based on a trajectory model. Group patterns of users are determined by distance threshold and minimum time duration. A trajectory model of user movement is adopted to save storage space and to cope with untracked or disconnected location data. To discover group patterns, we propose ATGP algorithm and TVG-growth that are derived from the Apriori and VG-growth algorithms respectively.
Discipline
Databases and Information Systems
Publication
Advances in Knowledge Discovery and Data Mining: 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKKD 2005)
First Page
713
Last Page
718
ISBN
9783540319351
Identifier
10.1007/11430919_82
Publisher
Springer Verlag
City or Country
Hanoi, Vietnam
Citation
HWANG, San-Yih; LIU, Ying-Han; CHIU, Jeng-Kuen; and LIM, Ee Peng.
Mining mobile group patterns: A trajectory-based approach. (2005). Advances in Knowledge Discovery and Data Mining: 9th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKKD 2005). 713-718.
Available at: https://ink.library.smu.edu.sg/sis_research/1034
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://doi.org/10.1007/11430919_82