6533b831fe1ef96bd1299951
RESEARCH PRODUCT
Multilingual Clustering of Streaming News
Guntis BarzdinsSebastião MirandaShay B. CohenArturs Znotinssubject
FOS: Computer and information sciencesComputer Science - Computation and LanguageInformation retrievalComputer scienceInformationSystems_INFORMATIONSTORAGEANDRETRIEVAL02 engineering and technologyClusteringMedia MonitoringComputer Science - Information RetrievalComputingMethodologies_PATTERNRECOGNITIONMultilingual Methods0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingCluster analysisComputation and Language (cs.CL)Information Retrieval (cs.IR)description
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-10-31 |