Online Near-Duplicate Detection of News Articles

Simon Rodier, Dave Carter


Abstract
Near-duplicate documents are particularly common in news media corpora. Editors often update wirefeed articles to address space constraints in print editions or to add local context; journalists often lightly modify previous articles with new information or minor corrections. Near-duplicate documents have potentially significant costs, including bloating corpora with redundant information (biasing techniques built upon such corpora) and requiring additional human and computational analytic resources for marginal benefit. Filtering near-duplicates out of a collection is thus important, and is particularly challenging in applications that require them to be filtered out in real-time with high precision. Previous near-duplicate detection methods typically work offline to identify all near-duplicate pairs in a set of documents. We propose an online system which flags a near-duplicate document by finding its most likely original. This system adapts the shingling algorithm proposed by Broder (1997), and we test it on a challenging dataset of web-based news articles. Our online system presents state-of-the-art F1-scores, and can be tuned to trade precision for recall and vice-versa. Given its performance and online nature, our method can be used in many real-world applications. We present one such application, filtering near-duplicates to improve productivity of human analysts in a situational awareness tool.
Anthology ID:
2020.lrec-1.156
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
1242–1249
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.156
DOI:
Bibkey:
Cite (ACL):
Simon Rodier and Dave Carter. 2020. Online Near-Duplicate Detection of News Articles. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 1242–1249, Marseille, France. European Language Resources Association.
Cite (Informal):
Online Near-Duplicate Detection of News Articles (Rodier & Carter, LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.156.pdf