Topic Retrospection with Storyline-based Summarization on News Reports

The electronics newspaper becomes a main source for online news readers. When facing the numerous stories of a series of events, news readers need some supports in order to review a topic in an efficient way. Besides identifying events and presenting the search results with news titles and keywords the TDT (Topic Detection and Tracking) is used to do, a summarized text to present event evolution is necessary for general news readers to review events under a news topic. This paper proposes a topic retrospection process and implements the SToRe system that identifies various events under a news topic, and composes a summary that news readers can get the sketch of event evolution in the topic. It consists of three main functions: event identification, main storyline construction and storyline-based summarization. The constructed main storyline can remove the irrelevant events and present a main theme. The summarization extracts the representative sentences and takes the main theme as the template to compose summary. The summarization not only provides enough information to comprehend the development of a topic, but also serves as an index to help readers to find more detailed information. A lab experiment is conducted to evaluate the SToRe system in the question-and-answer (Q&A) setting. The experimental results show that the SToRe system enables news readers to effectively and efficiently capture the evolution of a news topic.