MSIP: Study on multi-source infection pattern mining algorithm in four-dimensional spacetime

The existing contagion patterns lack the mining of dynamic multi-source infection events in real four-dimensional space-time, which reduces the applicability of the current research results. To address the shortcomings and challenges of existing research work, we investigate the multi-source infection pattern mining algorithm for infectious dynamics in four-dimensional space-time. In this paper, the multi-source infection pattern (MSIP) model is first defined in four-dimensional spacetime. The proposed model considers elements that are more accurate to the real environment, including multi-source infection, movement trajectory, and spatio-temporal dimension. The infection pattern mining algorithm based on opportunity (MABO) is proposed under the MSIP model. The result of the experiment demonstrates that MABO performs effectively, which can mine more infected events under multi-source infection conditions.