Title: TRAJECTORIES' CLASSIFICATION TO ENHANCE DECISION MAKING

Year of Publication: 2013
Page Numbers: 49-56
Authors: Wided Oueslati, Jalel Akaichi
Conference Name: The Second International Conference on Digital Enterprise and Information Systems (DEIS2013)
- Malaysia

Abstract:


Decision support systems such as trajectory data warehouse are based on the fast and the best decisions that are becoming the means of success in many domains. However, the best and the fast decisions requires consistent and meaningful data, therefore the idea is to select only specific and interesting data from the whole trajectory data stored in the trajectory data warehouse. The classification or the clustering of trajectory data is the best solution in this case. The aim of this paper is to propose a new classification of trajectories of moving objects based on some criteria. The classification will appear in the conceptual modeling of the trajectory data warehouse and will play an important role in the trajectory data analysis process.