Large-Scale Information Dissemination Algorithm Based on Random Mapping

In light of the inefficiency in managing and distributing large-scale information, this paper proposes a large-scale information publish-subscribe workflow model based on the publish-subscribe pattern. Furthermore, it introduces an evaluation indicator system for distribution efficiency, leveraging the Analytic Hierarchy Process to guide decision-making in large-scale information distribution processes. Additionally, a text matching algorithm based on random mapping is devised. This algorithm capitalizes on the effectiveness of hash tables and state information to enable efficient matching between documents and subscription information. Experimental results validate a significant improvement in matching efficiency by this algorithm, highlighting its practical value.