A Model for Enriching Trajectories with Semantic Geographical Information

Abstract

The collection of moving ob ject data is becoming more and more common, and therefore there is an increasing need for the efficient analysis and knowledge extraction of these data in different application domains. Tra jectory data are normally available as sample points, and do not carry se- mantic information, which is of fundamental importance for the comprehension of these data. Therefore, the analysis of tra jectory data becomes expensive from a computational point of view and complex from a user’s perspective. En- riching tra jectories with semantic geographical information may simplify queries, analysis, and mining of moving ob- ject data. In this paper we propose a data preprocessing model to add semantic information to tra jectories in order to facilitate tra jectory data analysis in different application domains. The model is generic enough to represent the im- portant parts of tra jectories that are relevant to the appli- cation, not being restricted to one specific application. We present an algorithm to compute the important parts and show that the query complexity for the semantic analysis of tra jectories will be significantly reduced with the proposed model.