  We describe a new method for summarizing similarities and differences in a
pair of related documents using a graph representation for text. Concepts
denoted by words, phrases, and proper names in the document are represented
positionally as nodes in the graph along with edges corresponding to semantic
relations between items. Given a perspective in terms of which the pair of
documents is to be summarized, the algorithm first uses a spreading activation
technique to discover, in each document, nodes semantically related to the
topic. The activated graphs of each document are then matched to yield a graph
corresponding to similarities and differences between the pair, which is
rendered in natural language. An evaluation of these techniques has been
carried out.
