|Author's Email Address
||This thesis had been viewed 5215 times. Download 19 times.|
|Type of Document
||Mining Mobile Group Patterns Using Trajectory Approximation|
|Date of Defense
||mobile group pattern
group pattern mining
mobile data mining
||In this paper, we present a novel approach to mine moving object group patterns from object movement database. At first, our approaches summarize the raw data in the source object movement database into trajectories, and then discover valid 2-groups mainly from the trajectory-based object movement database. |
We propose two trajectory conversion methods, namely linear regression and vector conversion. We further propose a trajectory based mobile group mining algorithm that is intended to reduce the overhead of mining 2-Group Patterns. The use of trajectories allows valid 2-groups to be mined using smaller number of summarized records (in trajectory model) and examining smaller number of candidate 2-groups.
Finally, we conduct series of comprehensive experiments to evaluate and compare the performances of the proposed methods with existing approaches that use source object movement database or other summarization techniques. The experimental results demonstrate the superior performance of our proposed approach.
||Fu-ren Lin - chair|
Wei-Chih Ping - co-chair
San -Yih Hwang - advisor
indicate in-campus access only|
|Date of Submission