HILBERT OPERATOR–BASED TRUST COMPUTATION IN COMPLEX NETWORKS VIA TENSOR STATE REPRESENTATION

Abstract

Trust evaluation plays a central role in complex networks or network-

drived systems such as social networks, collaborative systems, and online

communities. Traditional trust models rely on heuristic propagation rules

that do not fully exploit netwrok heterogeneous data. This paper pro-

poses a mathematical framework for trust computation based on Hilbert

space operators. The framework transforms user features of networks into

tensor representations, constructs trust states from these tensors, and

models trust propagation through bounded operators in Hilbert spaces.

A numerical example illustrates the complete pipeline from features to

trust scores.