A hybrid statistical/linguistic approach to headline generation

In this paper, we present the HybridTrim system, which uses a machine learning technique to combine linguistic, statistical and positional information to identify topic labels for headlines in a text. We compare our system with the Topiary system which, in contrast, uses a statistical learning approach to finding topic descriptors for headlines. Both of these systems combine these topic descriptors with a compressed version of the lead sentence. The performance of these systems is evaluated using the ROUGE evaluation suite on the DUC 2004 news stories collection.