6334491
doi
10.5281/zenodo.6334491
oai:zenodo.org:6334491
user-eu
Pivovarova, Lidia
University of Helsinki
Boggia, Michele
University of Helsinki
Ivanova, Sardana
University of Helsinki
Multilingual Topic Labelling of News Topics using Ontological Mapping
Zosa, Elaine
University of Helsinki
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
topic labelling, ontology linking, cross-lingual embeddings
<p>The large volume of news produced daily makes topic modelling useful for analysing topical trends. A topic is usually represented by a ranked list of words but this can be dicult and time-consuming for humans to interpret. Therefore, various methods have been proposed to generate labels that capture the semantic content of a topic. However, there has been no work so far on coming up with multilingual labels which can be useful for exploring multilingual news collections. We propose an ontological mapping method that maps topics to concepts in a language-agnostic news ontology. We test our method on Finnish and English topics and show that it performs on par with state-of-the-art label generation methods, is able to produce multilingual labels, and can be applied to topics from languages that have not been seen during training without any modifications.</p>
Zenodo
2022-03-07
info:eu-repo/semantics/conferencePaper
6334490
user-eu
award_title=NewsEye: A Digital Investigator for Historical Newspapers; award_number=770299; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/770299; funder_id=00k4n6c32; funder_name=European Commission;
1646704139.707947
233230
md5:538fbeb3809b6a04fe1e761701858170
https://zenodo.org/records/6334491/files/ECIR___news_topic_label_generation.pdf
public
10.5281/zenodo.6334490
isVersionOf
doi