A geo-computational algorithm for exploring the structure of diffusion progression in time and space.

ABSTRACT: A diffusion process can be considered as the movement of linked events through space and time. Therefore, space-time locations of events are key to identify any diffusion process. However, previous clustering analysis methods have focused only on space-time proximity characteristics, neglecting the temporal lag of the movement of events. We argue that the temporal lag between events is a key to understand the process of diffusion movement. Using the temporal lag could help to clarify the types of close relationships. This study aims to develop a data exploration algorithm, namely the TrAcking Progression In Time And Space (TaPiTaS) algorithm, for understanding diffusion processes. Based on the spatial distance and temporal interval between cases, TaPiTaS detects sub-clusters, a group of ev

SUBMITTER: Chin WC 

PROVIDER: S-EPMC5626785 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature