Automatically constructing semantic link network on documents

Knowing semantic links among resources is the basis of realizing machine intelligence over large-scale resources. Discovering semantic links among resources with limited human interference is a challenge issue. This paper proposes an approach to automatically discovering and predicting semantic links in a document set based on a model of document semantic link network (SLN). The approach has the following advantages: it supports probabilistic relational reasoning; SLNs and the relevant rules automatically evolve; and, it can adapt to the update of the adopted techniques. The approach can support cyber space applications, such as documentation recommendation and relational queries, on large documents. Copyright (C) 2010 John Wiley & Sons, Ltd.