Automatic headline generation for newspaper stories

In this paper we propose a novelapplication of Hidden Markov Models to
automatic generation of informative headlines
for English texts. We propose four decoding
parameters to make the headlines appear more
like Headlinese, the language of informative
newspaper headlines. We also allow for
morphological variation in words between
headline and story English. Informal and formal
evaluations indicate that our approach produces
informative headlines, mimicking a Headlinese
style generated by humans.