Spatial uncertainty trajectory dataset mining based on two-stages dynamic division

Liang Wang, Mei Wang, Hucheng He

科研成果: 期刊稿件文章同行评审

摘要

Due to the measurement precision, transmission delay and so on, we could only obtain uncertainty position information of moving objects. Spatial uncertainty trajectory data is uncertain in location of mobile objects. It is leading to the challenge of modeling uncertainty trajectory data and mining usable knowledge about movement pattern. In this paper, we propose a two-stages dynamic division method to dealing with the spatial uncertainty trajectory. The approach presents the notions of adjacent boundary cells and shared cells, and merges these cells into basic cells through distance and density membership degree. A comprehensive performance study on synthetic datasets shows that the proposed method in both effectiveness and scalability.

源语言英语
页(从-至)1897-1904
页数8
期刊Journal of Information and Computational Science
12
5
DOI
出版状态已出版 - 20 3月 2015
已对外发布

指纹

探究 'Spatial uncertainty trajectory dataset mining based on two-stages dynamic division' 的科研主题。它们共同构成独一无二的指纹。

引用此