@inproceedings{laban-hearst-2017-newslens,
title = "news{L}ens: building and visualizing long-ranging news stories",
author = "Laban, Philippe and
Hearst, Marti",
editor = "Caselli, Tommaso and
Miller, Ben and
van Erp, Marieke and
Vossen, Piek and
Palmer, Martha and
Hovy, Eduard and
Mitamura, Teruko and
Caswell, David",
booktitle = "Proceedings of the Events and Stories in the News Workshop",
month = aug,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W17-2701",
doi = "10.18653/v1/W17-2701",
pages = "1--9",
abstract = "We propose a method to aggregate and organize a large, multi-source dataset of news articles into a collection of major stories, and automatically name and visualize these stories in a working system. The approach is able to run online, as new articles are added, processing 4 million news articles from 20 news sources, and extracting 80000 major stories, some of which span several years. The visual interface consists of lanes of timelines, each annotated with information that is deemed important for the story, including extracted quotations. The working system allows a user to search and navigate 8 years of story information.",
}
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<abstract>We propose a method to aggregate and organize a large, multi-source dataset of news articles into a collection of major stories, and automatically name and visualize these stories in a working system. The approach is able to run online, as new articles are added, processing 4 million news articles from 20 news sources, and extracting 80000 major stories, some of which span several years. The visual interface consists of lanes of timelines, each annotated with information that is deemed important for the story, including extracted quotations. The working system allows a user to search and navigate 8 years of story information.</abstract>
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%0 Conference Proceedings
%T newsLens: building and visualizing long-ranging news stories
%A Laban, Philippe
%A Hearst, Marti
%Y Caselli, Tommaso
%Y Miller, Ben
%Y van Erp, Marieke
%Y Vossen, Piek
%Y Palmer, Martha
%Y Hovy, Eduard
%Y Mitamura, Teruko
%Y Caswell, David
%S Proceedings of the Events and Stories in the News Workshop
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F laban-hearst-2017-newslens
%X We propose a method to aggregate and organize a large, multi-source dataset of news articles into a collection of major stories, and automatically name and visualize these stories in a working system. The approach is able to run online, as new articles are added, processing 4 million news articles from 20 news sources, and extracting 80000 major stories, some of which span several years. The visual interface consists of lanes of timelines, each annotated with information that is deemed important for the story, including extracted quotations. The working system allows a user to search and navigate 8 years of story information.
%R 10.18653/v1/W17-2701
%U https://aclanthology.org/W17-2701
%U https://doi.org/10.18653/v1/W17-2701
%P 1-9
Markdown (Informal)
[newsLens: building and visualizing long-ranging news stories](https://aclanthology.org/W17-2701) (Laban & Hearst, EventStory 2017)
ACL