In this paper, we propose a new algorithm of summarization which targets a new kind of structured contents. The structured content, which is to be created by semantic authoring, consists of sentenses and rhetorical relation among sentences: It is represented by a graph, where a node is a sentence and an edge is a rhetorical relation. We simulate creating this content graph by using news paper articles that are annotated rhetorical relations by a GDA tagset. Our summarization method basically uses spreading activation over the content graph, followed by particular postprocesses to increase readability of the resultant summary. Experimental evaluation shows our method is at least equal to or better than Lead method for summarizing news paper articles.
|ジャーナル||Transactions of the Japanese Society for Artificial Intelligence|
|出版物ステータス||Published - 2005 5 24|
ASJC Scopus subject areas
- Artificial Intelligence