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Multilingual Clustering of Streaming News

Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Sebastiao Miranda
  • Arturs Znotins
  • Shay Cohen
  • Guntis Barzdins

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Documents

http://aclweb.org/anthology/D18-1483
https://aclanthology.coli.uni-saarland.de/papers/D18-1483/d18-1483
Original languageEnglish
Title of host publication2018 Conference on Empirical Methods in Natural Language Processing
Place of PublicationBrussels, Belgium
PublisherAssociation for Computational Linguistics
Pages4535-4544
Number of pages10
Publication statusPublished - Nov 2018
Event2018 Conference on Empirical Methods in Natural Language Processing - Square Meeting Center, Brussels, Belgium
Duration: 31 Oct 20184 Nov 2018
http://emnlp2018.org/

Conference

Conference2018 Conference on Empirical Methods in Natural Language Processing
Abbreviated titleEMNLP 2018
CountryBelgium
CityBrussels
Period31/10/184/11/18
Internet address

Abstract

Clustering news across languages enables efficient media monitoring by aggregating articles from multilingual sources into coherent stories. Doing so in an online setting allows scalable processing of massive news streams. To this end, we describe a novel method for clustering an incoming stream of multilingual documents into monolingual and crosslingual story clusters. Unlike typical clustering approaches that consider a small and known number of labels, we tackle the problem of discovering an ever growing number of cluster labels in an online fashion, using real news datasets in multiple languages. Our method is simple to implement, computationally efficient and produces state-of-the-art results on datasets in German, English and Spanish.

Event

2018 Conference on Empirical Methods in Natural Language Processing

31/10/184/11/18

Brussels, Belgium

Event: Conference

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