Abstract
Since a story consists of several scenes and topics, for making a summary of a story, it is essential to get hold of relations between topics. This means that to make a coherent summary is a key issue for informative summary of a story. On the basis of this background, in this paper, the author proposes a method to produce a coherent summary of story focusing on extracting (1) topic block that consists of sentences that may be written on the same topic, and (2) complement sentences that may express change of scenes. They are extracted on the basis of automatic topic recognition and identification of characters. The experimental results of summarization for 9 stories show the proposed method produces easier-to-follow summaries than those of a tf·idf based model.
