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Storyline-based summarization for news topic retrospection

Electronics newspapers gradually become main sources for news readers. When facing the numerous reports on a series of events in a topic, a summary of stories from news reports will benefit news readers in reviewing the news topic efficiently. Besides identifying events and presenting news titles an...

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Published in:Decision Support Systems 2008-06, Vol.45 (3), p.473-490
Main Authors: Lin, Fu-ren, Liang, Chia-Hao
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Language:English
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cited_by cdi_FETCH-LOGICAL-c452t-a45a18a880ee9a831c151b3c8bdef4cd5ae1e4cbf38e61132197204094d622e93
cites cdi_FETCH-LOGICAL-c452t-a45a18a880ee9a831c151b3c8bdef4cd5ae1e4cbf38e61132197204094d622e93
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description Electronics newspapers gradually become main sources for news readers. When facing the numerous reports on a series of events in a topic, a summary of stories from news reports will benefit news readers in reviewing the news topic efficiently. Besides identifying events and presenting news titles and keywords the TDT (Topic Detection and Tracking) techniques are 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 ( Story-line based Topic Retrospection) 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 storyline-based summarization extracts the representative sentences and takes the main theme as the template to compose the summary. The storyline summary not only provides readers enough information to understand the development of a news topic, but also serves as an index for readers to search corresponding news reports. Following a design science paradigm, a lab experiment is conducted to evaluate the SToRe system in the question-and-answer (Q&A) setting. The experimental results show that SToRe enables news readers to effectively and efficiently capture the evolution of a news topic.
doi_str_mv 10.1016/j.dss.2007.06.009
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ispartof Decision Support Systems, 2008-06, Vol.45 (3), p.473-490
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language eng
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subjects Decision support systems
Event threading
Information management
Studies
Summarization
Topic detection and tracking (TDT)
Topic retrospection
title Storyline-based summarization for news topic retrospection
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