Automatic Annotation of Corpora for Text Summarisation: A Comparative Study

This paper presents two methods which automatically produce annotated corpora for text summarisation on the basis of human abstracts. Both methods identify a set of sentences from the document which conveys the information in the human produced best. The first method relies on a greedy algorithm, whilst the second one uses a genetic algorithm. The methods allow to specify the number of sentences to be annotated, which constitutes an advantage over the existing methods. Comparison between the two approaches investigated here revealed that the genetic algorithm is appropriate in cases where the number of sentences to be annotated is less than the number of sentences in an ideal gold standard with no length restrictions, whereas the greedy algorithm should be used in other cases.

• Type: Conference
• Year: 2005
• Where: CICLING
• Authors: Constantin Orasan
• Keywords: CICLING 2005, Genetic Algorithm, Greedy Algorithm, Natural Language Processing, first Method Relies