@article{Berven2020,

title = {A knowledge-graph platform for newsrooms},

author = {Arne Berven and Ole A. Christensen and Sindre Moldeklev and Andreas L. Opdahl and Kjetil A. Villanger },

url = {https://reader.elsevier.com/reader/sd/pii/S0166361520305558?token=F8A21A513C97BFF598C2755575B3C89174B3D404E2EDDD23EC37966A2754ACA1700011EBBCF52ADE2845ADBC12D40041},

doi = {https://doi.org/10.1016/j.compind.2020.103321},

year  = {2020},

date = {2020-12-01},

urldate = {2020-12-01},

journal = {Computers in Industry},

volume = {123},

number = {103321},

abstract = {Journalism is challenged by digitalisation and social media, resulting in lower subscription numbers and reduced advertising income. Information and communication techniques (ICT) offer new opportunities. Our research group is collaborating with a software developer of news production tools for the international market to explore how social, open, and other data sources can be leveraged for journalistic purposes. We have developed an architecture and prototype called News Hunter that uses knowledge graphs, natural-language processing (NLP), and machine learning (ML) together to support journalists. Our focus is on combining existing data sources and computation and storage techniques into a flexible architecture for news journalism. The paper presents News Hunter along with plans and possibilities for future work.},

note = {Pre SFI},

keywords = {Computational journalism, Journalistic knowledge platforms, Knowledge graphs, Machine learning (ML), Natural-language processing (NLP), Newsroom systems, Ontology, OWL, RDF, Semantic technologies, WP3: Media Content Production and Analysis},

pubstate = {published},

tppubtype = {article}

}