Creating a natural language summary from a compressed causal graph

The aim of this paper is to introduce a set of procedures capable of produce a text summary from a causal graph. In previous works we have presented several algorithms to extract causal information from text documents by means of a semi-automatic process. As result we obtained a causal graph connecting concepts related to a given topic. In this paper we present a procedure capable of generating an abstract of that causal graph introducing new words and expressions similar to the ones appearing in the nodes of the graph.