  We study automatic title generation for a given block of text and present a
method called DTATG to generate titles. DTATG first extracts a small number of
central sentences that convey the main meanings of the text and are in a
suitable structure for conversion into a title. DTATG then constructs a
dependency tree for each of these sentences and removes certain branches using
a Dependency Tree Compression Model we devise. We also devise a title test to
determine if a sentence can be used as a title. If a trimmed sentence passes
the title test, then it becomes a title candidate. DTATG selects the title
candidate with the highest ranking score as the final title. Our experiments
showed that DTATG can generate adequate titles. We also showed that
DTATG-generated titles have higher F1 scores than those generated by the
previous methods.
