Exploring the Interactions of Storylines from Informative News Events

• 作 者: 胡珀 黄民烈 朱小燕
• 出 处: 计算机科学技术学报（英文版）
• 发表日期: 2004年期
• 关键词: text mining storyline interaction informative event coherence user preference
• 基金项目: the Tsinghua University Initiative Scientific Research Program under;the Beijing Higher Education Young Elite Teacher Project;the National Natural Science Foundation of China under;Supported by the Na

Today’s news readers can be easily overwhelmed by the numerous news articles online. To cope with information overload, online news media publishes timelines for continuously developing news topics. However, the timeline summary does not show the relationship of storylines, and is not intuitive for readers to comprehend the development of a complex news topic. In this paper, we study a novel problem of exploring the interactions of storylines in a news topic. An interaction of two storylines is signified by informative news events that play a key role in both storylines. Storyline interactions can indicate key phases of a news topic, and reveal the latent connections among various aspects of the story. We address the coherence between news articles which is not considered in traditional similarity-based methods, and discover salient storyline interactions to form a clear, global picture of the news topic. User preference can be naturally integrated into our method to generate query-specific results. Comprehensive experiments on ten news topics show the effectiveness of our method over alternative approaches.