11th Pacific-Asia Conference on Information Systems 144. Individualized Storyline-based News Topic Retrospection

It takes a great effort for common news readers to track events promptly, and not to mention that they can retrospect them precisely after it occurred for a long time period. Although topic detection and tracking techniques have been developed to promptly identify and keep track of similar events in a topic and monitor their progress, the cognitive load remains for a reader to digest these reports. A storyline-based summarization may facilitate readers to recall occurred events in a topic by extracting informative sentences of news reports to compose a concise summary with essential episodes. This paper proposes SToRe (Story-line based Topic Retrospection), that identifies events from news reports and composes a storyline summary to portray the event evolution in a topic. It consists of three main functions: event identification, main storyline construction and storyline-based summarization. The main storyline guides the extraction of representative sentences from news articles to summarize occurred events. This study demonstrates that different topi