The invention discloses a multi-
modal network fusion method and
system for an HIV infection
source tracking and intervention strategy. The method comprises the steps that an index immediate network adversarial generative
graph model is utilized to construct a multi-
modal network for HIV transmission; identifying key nodes in the
virus transmission process; and based on the key nodes of the multi-
modal network, implementing an intervention strategy and evaluating an
intervention effect. According to the method, the unified multi-modal
complex network is constructed by fusing the online
social network, the offline behavior network and the HIV
molecular network, so that the problem of insufficient
data integration in the prior art is solved. A multi-modal node importance
sorting algorithm based on
deep learning is introduced, and key propagation nodes in the network are accurately identified in combination with a
reinforcement learning technology. And a partition nested random network search and
data driven deep
reinforcement learning algorithm is adopted, so that the calculation complexity of key node identification and intervention strategy optimization is remarkably reduced.