The present application relates to the field of intelligent printing and typesetting technology, and in particular to a printed matter typesetting
system and method based on intelligent recognition, which includes: a
spatial relationship extractor, a
potential field layout engine, a morphological adapter, and an intelligent recognition module; wherein the
spatial relationship extractor generates a semantic
topological graph through a graph neural network, wherein the nodes contain
content type and media affinity features, and the edge weights are calculated by a composite of
semantic association strength and
spatial dependency coefficient; the
potential field layout engine solves node coordinates through a
gradient descent method based on
gravitational potential energy terms and repulsive
potential energy terms; the morphological adapter performs
topological transformation according to the
media type, with position locking applied to printed media and associated node folding constraints enabled for
electronic media; and the intelligent recognition module integrates a multimodal recognition model and outputs a content
feature vector with confidence. Thus, the
system solves the problems of weak content association, low
layout optimization efficiency, poor media adaptability, and insufficient intelligence in the prior art.