Automatically Discovering Semantic Links among Documents

Knowing semantic links among documents is the basis for intelligent applications over large-scale document resources. Discovering these semantic links with little human interference is a challenge issue. This paper proposes an approach to automatically discover semantic links in document set based on a probabilistic documentary semantic link network model. The approach has the following advantages: 1) It supports probabilistic relational reasoning. 2) The semantic link networks and relevant rules automatically evolve. 3) It does not rely on any predefined ontology. 4) It can adapt to the update of the adopted techniques. Experiments on document sets of different types (scientific papers and Web pages) and different scales show the proposed approach feasible. The approach can be used to automatically construct semantic overlays on large document sets to support advanced applications like various relational queries on scientific documents.