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dTexSL: A dynamic disaster textual storyline generating framework

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Abstract

Effectively capturing the status information and improving situational awareness is the most important task in disaster information management. Due to the rapid increase of online information, this task becomes very challenging. Existing information retrieval and text summarization methods can solve information overload problem to some extent, however, they suffer from some limitations: lacking theme structure, ignoring spatial information, and unable to update information on the real time events. In this paper, we propose a dynamic disaster storyline generation framework, which generates a global storyline describing the evolution of the disaster events in the high-level layer and provides condensed information about specific regions affected by the disaster in the local-level layer. The proposed framework considers both uniqueness and relevance for representative document selection, uses Maximal Marginal Relevance to generate summaries from each local document set, and utilizes dynamic Steiner tree to implement the information update. Comprehensive experiments on typhoons data sets demonstrate the effectiveness of the proposed methods in each level and the overall framework.

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Acknowledgments

This work is supported by the Natural Science Foundation of Fujian Province (China) under Grant No. 2017J01118 and Shenzhen Science and Technology Planning Program under Grant No. JCYJ20170307141019252.

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Authors and Affiliations

  1. Automation Department of Xiamen University, Xiamen, China

    Ruifeng Yuan & Qifeng Zhou

  2. Shenzhen Research Institute of Xiamen University, Xiamen, China

    Ruifeng Yuan & Qifeng Zhou

  3. Uber Technologies, Inc, San Francisco, CA, USA

    Wubai Zhou

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  1. Ruifeng Yuan
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  2. Qifeng Zhou
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  3. Wubai Zhou
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Correspondence to Qifeng Zhou.

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This article belongs to the Topical Collection: Special Issue on Big Data for Effective Disaster Management

Guest Editors: Xuan Song, Song Guo, and Haizhong Wang

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Yuan, R., Zhou, Q. & Zhou, W. dTexSL: A dynamic disaster textual storyline generating framework. World Wide Web 22, 1913–1933 (2019). https://doi.org/10.1007/s11280-018-0640-8

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