Abstract
Media vehicles play an essential role in investigating events and keeping the public informed. Indirectly, logs of daily events made by newspapers and magazines have been built rich collections of data that can be used by lots of professionals such as economists, historians, and political scientists. However, exploring these logs with traditional search engines has become impractical for more demanding users. In this paper, we propose StoryTracker, a temporal exploration tool that helps users query news collections. We focus our efforts (i) to allow users to make queries by adding information from documents represented by word embbedings and (ii) to develop a strategy for retrieving temporal information to generate timelines and present them using a suitable interface for temporal exploration. We evaluated our solution using a real database of articles from a huge Brazilian newspaper and showed that our tool can trace different timelines, covering different subtopics of the same theme.
Supported by CAPES, CNPq, Finep, Fapesp and Fapemig.
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Notes
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The code is available at https://github.com/warSantos/StoryTracker.git.
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Acknowledgments
This project has partially supported by Huawei do Brasil Telecomunicações Ltda (Fundunesp Process # 3123/2020), FAPEMIG, and CAPES.
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Santos, W., Fazzion, E., Tuler, E., Dias, D., Guimarães, M., Rocha, L. (2021). StoryTracker: A Semantic-Oriented Tool for Automatic Tracking Events by Web Documents. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12951. Springer, Cham. https://doi.org/10.1007/978-3-030-86970-0_10
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